Please find updated publications list here.
In Preparation or Unpublished
Gershenson, C. (2007).
Design and Control of Self-organizing Systems.
Vrije Universiteit Brussel.
Abstract: Complex systems are usually difficult to design and control. There are several particular methods for coping with complexity, but there is no general approach to build complex systems. In this thesis I propose a methodology to aid engineers in the design and control of complex systems. This is based on the description of systems as self-organizing. Starting from the agent metaphor, the methodology proposes a conceptual framework and a series of steps to follow to find proper mechanisms that will promote elements to find solutions by actively interacting among themselves. The main premise of the methodology claims that reducing the “friction” of interactions between elements of a system will result in a higher “satisfaction” of the system, i.e. better performance.
A general introduction to complex thinking is given, since designing self-organizing systems requires a non-classical thought, while practical notions of complexity and self-organization are put forward. To illustrate the methodology, I present three case studies. Self-organizing traffic light controllers are proposed and studied with multi-agent simulations, outperforming traditional methods. Methods for improving communication within self-organizing bureaucracies are advanced, introducing a simple computational model to illustrate the benefits of self-organization. In the last case study, requirements for self-organizing artifacts in an ambient intelligence scenario are discussed. Philosophical implications of the conceptual framework are also put forward.
Gershenson, C. (2002d).
A Comparison of Different Cognitive Paradigms
Using Simple Animats in a Virtual Laboratory,
with Implications to the Notion of Cognition.
Unpublished MSc Thesis.
University of Sussex.
In this thesis I present a virtual laboratory which implements five different
models for controlling animats: a rule-based system, a behaviour-based system, a
concept-based system, a neural network, and a Braitenberg architecture. Through
different experiments, I compare the performance of the models and conclude that
there is no “best” model, since different models are better for different things in
different contexts. The models I chose, although quite simple, represent different
approaches for studying cognition. Using the results as an empirical philosophical
aid, I note that there is no “best” approach for studying cognition, since different
approaches have all advantages and disadvantages, because they study different
aspects of cognition from different contexts. This has implications for current
debates on “proper” approaches for cognition: all approaches are a bit proper, but
none will be “proper enough”. I draw remarks on the notion of cognition abstracting
from all the approaches used to study it, and propose a simple classification for
different types of cognition.
Gershenson, C. (2001a). Artificial
Societies of Intelligent Agents. Unpublished BEng Thesis. Fundación
Arturo Rosenblueth, México.
In this thesis we present our work, where we developed artificial societies of intelligent agents, in order to understand and simulate adaptive behaviour and social processes. We obtain this in three parallel ways: First, we present a behaviours production system capable of reproducing a high number of properties of adaptive behaviour and of exhibiting emergent lower cognition. Second, we introduce a simple model for social action, obtaining emergent complex social processes from simple interactions of imitation and induction of behaviours in agents. And third, we present our approximation to a behaviours virtual laboratory, integrating our behaviours production system and our social action model in animats. In our behaviours virtual laboratory, the user can perform a wide variety of experiments, allowing him or her to test the properties of our behaviours production system and our social action model, and also to understand adaptive and social behaviour. It can be accessed and downloaded through the Internet. Before presenting our proposals, we make an introduction to artificial intelligence and behaviour-based systems, and also we give notions of complex systems and artificial societies. In the last chapter of the thesis, we present experiments carried out in our behaviours virtual laboratory showing the main properties of our behaviours production system, of our social action model, and of our behaviours virtual laboratory itself. Finally, we discuss about the understanding of adaptive behaviour as a path for understanding cognition and its evolution.
Bettstetter, C. & C. Gershenson (Eds.) (2011). Self-Organizing Systems 5th International Workshop, IWSOS 2011, Karlsruhe, Germany, February 23-24, 2011, Proceedings. Springer LNCS 6557. ISBN: 978-3-642-19166-4.
This book constitutes the refereed proceedings of the 5th International Workshop on Self-Organizing Systems, IWSOS 2011, held in Karlsruhe, Germany, in February 2011.
The 9 revised full papers presented together with 1 invited paper were carefully selected from 25 initial submissions. It was the 5th workshop in a series of multidisciplinary events dedicated to self-organization in networked systems with main focus on communication and computer networks. The papers address theoretical aspects of self-organization as well as applications in communication and computer networks and robot
Gershenson, C. (Ed.) (2008).
Complexity: 5 Questions.
Automatic Peess / VIP, ISBN 8792130135.
This volume consists of short, interview-style contributions by leading figures in the field of complexity, based on five questions. The answers trace their personal experience and expose their views on the definition, aspects, problems and future of complexity.
The aim of the book is to bring together the opinions of researchers with different backgrounds on the emerging study of complex systems. In this way, we will see similarities and differences, agreements and debates among the approaches of different schools.
Contributors: Peter M. Allen, Philip W. Anderson, W. Brian Arthur, Yaneer Bar-Yam, Eric Bonabeau, Paul Cilliers, Jim Crutchﬁeld, Bruce Edmonds, Nigel Gilbert, Hermann Haken, Francis Heylighen, Bernardo A. Huberman, Stuart A. Kauffman, Seth Lloyd, Gottfried Mayer-Kress, Melanie Mitchell, Edgar Morin, Mark Newman, Grégoire Nicolis, Jordan B. Pollack, Peter Schuster, Ricard V. Solé, Tamás Vicsek, Stephen Wolfram.
Gershenson, C. (2007).
Design and Control of Self-organizing Systems.
CopIt ArXives, Mexico. TS0002EN.
Abstract: Complex systems are usually difficult to design and control. There are several particular methods for coping with complexity, but there is no general approach to build complex systems. In this book I propose a methodology to aid engineers in the design and control of complex systems. This is based on the description of systems as self-organizing. Starting from the agent metaphor, the methodology proposes a conceptual framework and a series of steps to follow to find proper mechanisms that will promote elements to find solutions by actively interacting among themselves.
- Gershenson, C., D. Aerts, and B. Edmonds (Eds.). (2007). Worldviews, Science, and Us: Philosophy and Complexity. World Scientific, Singapore.
Gershenson, C. & D. A. Rosenblueth (In Press).
Self-organizing traffic lights at multiple-street intersections,
The elementary cellular automaton following rule 184 can mimic particles flowing in one direction at a constant speed. Therefore, this automaton can model highway traffic qualitatively. In a recent paper, we have incorporated intersections regulated by traffic lights to this model using exclusively elementary cellular automata. In such a paper, however, we only explored a rectangular grid. We now extend our model to more complex scenarios using an hexagonal grid. This extension shows first that our model can readily incorporate multiple-way intersections and hence simulate complex scenarios. In addition, the current extension allows us to study and evaluate the behavior of two different kinds of traffic-light controller for a grid of six-way streets allowing for either two- or three-street intersections: a traffic light that tries to adapt to the amount of traffic (which results in self-organizing traffic lights) and a system of synchronized traffic lights with coordinated rigid periods (sometimes called the “green-wave” method). We observe a tradeoff between system capacity and topological complexity. The green-wave method is unable to cope with the complexity of a higher-capacity scenario, while the self-organizing method is scalable, adapting to the complexity of a scenario and exploiting its maximum capacity. Additionally, in this article, we propose a benchmark, independent of methods and models, to measure the performance of a traffic-light controller comparing it against a theoretical optimum.
Gershenson, C. (2011).
Self-Organization Leads to Supraoptimal Performance in Public Transportation Systems.. PLoS ONE 6(6): e21469.
The performance of public transportation systems affects a large part of the population. Current theory assumes that passengers are served optimally when vehicles arrive at stations with regular intervals. In this paper, it is shown that self-organization can improve the performance of public transportation systems beyond the theoretical optimum by responding adaptively to local conditions. This is possible because of a “slower-is-faster” effect, where passengers wait more time at stations but total travel times are reduced. The proposed self-organizing method uses “antipheromones” to regulate headways, which are inspired by the stigmergy (communication via environment) of some ant colonies.
Gershenson, C. (In Press).
Guiding the Self-organization of Random Boolean Networks,
Theory in Biosciences. DOI: 10.1007/s12064-011-0144-x
Random Boolean networks (RBNs) are models of genetic regulatory networks. It is useful to describe RBNs as self-organizing systems to study how changes in the nodes and connections affect the global network dynamics. This article reviews eight different methods for guiding the self-organization of RBNs. In particular, the article is focussed on guiding RBNs towards the critical dynamical regime, which is near the phase transition between the ordered and dynamical phases. The properties and advantages of the critical regime for life, computation, adaptability, evolvability, and robustness are reviewed. The guidance methods of RBNs can be used for engineering systems with the features of the critical regime, as well as for studying how natural selection evolved living systems, which are also critical.
Gershenson, C. & M. Prokopenko (2011).
Artificial Life 17(4):259–261.
Poblanno-Balp, R. & C. Gershenson (2011).
Modular Random Boolean Networks,
Artificial Life 17(4):331–351.
Random Boolean networks (RBNs) have been a popular model of genetic regulatory networks for more than four decades. However, most RBN studies have been made with random topologies, while real regulatory networks have been found to be modular.
In this work, we extend classical RBNs to define modular RBNs.
Statistical experiments and analytical results show that modularity has a strong effect on the properties of RBNs. In particular, modular RBNs have more attractors and are closer to criticality when chaotic dynamics would be expected, compared to classical RBNs.
Gershenson, C. (2011).
The sigma profile: A formal tool to study organization and its evolution at multiple scales,
The σ profile is presented as a tool to analyze the organization of systems at different scales, and how this organization changes in time. Describing structures at different scales as goal-oriented agents, one can define σ ∈ [0,1] (satisfaction) as the degree to which the goals of each agent at each scale have been met. σ reflects the organization degree at that scale. The σ profile of a system shows the satisfaction at different scales, with the possibility to study their dependencies and evolution. It can also be used to extend game theoretic models. The description of a general tendency on the evolution of complexity and cooperation naturally follows from the σ profile. Experiments on a virtual ecosystem are used as illustration.
Rosenblueth, D. A. & C. Gershenson (2011).
A model of city traffic based on elementary cellular automata,
Complex Systems 19(4):305-322.
There are several highway traffic models proposed based on
The simplest one is elementary cellular automaton rule 184.
We extend this model to city traffic with cellular automata
coupled at intersections using only rules 184, 252, and 136. We study the model properties simulating a single intersection. Velocity-density and flux-density diagrams are used to describe the different dynamical phases of the model and the dependencies on different parameters. The model is promising for studying the problem of traffic light coordination of very large systems.
Gershenson, C. (2011).
What Does Artificial Life Tell Us About Death?,
International Journal of Artificial Life Research 2(3):1-5.
Gershenson, C. (2011).
Epidemiología y las Redes Sociales,
Cirugía y Cirujanos,79(3).
- Pineda. L.A., I. V. Meza, H. H. Avilés, C. Gershenson, C. Rascón, M. Alvarado & L. Salinas (2011). IOCA: An Interaction-Oriented Cognitive Architecture, Research in Computer Science 54:273-284.
Gershenson, C. (2010).
Computing Networks: A General Framework to Contrast Neural and Swarm Cognitions,
Paladyn, Journal of Behavioral Robotics, 1(2):147-153.
This paper presents the Computing Networks (CNs) framework. CNs are used to generalize neural and swarm architectures. Artificial neural networks, ant colony optimization, particle swarm optimization, and realistic biological models are used as examples of instantiations of CNs. The description of these architectures as CNs allows their comparison. Their differences and similarities allow the identification of properties that enable neural and swarm architectures to perform complex computations and exhibit complex cognitive abilities. In this context, the most relevant characteristics of CNs are the existence multiple dynamical and functional scales. The relationship between multiple dynamical and functional scales with adaptation, cognition (of brains and swarms) and computation is discussed.
Gershenson, C. and L. A. Pineda (2009). Why Does Public Transport Not Arrive on Time? The Pervasiveness of Equal Headway Instability.
PLoS ONE 4(10): e7292
The equal headway instability phenomenon is pervasive in public transport systems. This instability is characterized by an aggregation of vehicles that causes inefficient service. While equal headway instability is common, it has not been studied independently of a particular scenario. However, the phenomenon is apparent in many transport systems and can be modeled and rectified in abstraction.
We present a multi-agent simulation where a default method with no restrictions always leads to unstable headways. We discuss two methods that attempt to achieve equal headways, called minimum and maximum. Since one parameter of the methods depends on the passenger density, adaptive versions—where the relevant parameter is adjusted automatically—are also put forward. Our results show that the adaptive maximum method improves significantly over the default method. The model and simulation give insights of the interplay between transport design and passenger behavior. Finally, we provide technological and social suggestions for engineers and passengers to help achieve equal headways and thus reduce delays.
The equal headway instability phenomenon can be avoided with the suggested technological and social measures.
- Gershenson, C. and T. Lenaerts (2008). Evolution of Complexity.
Artificial Life 14(3):241–243
Gershenson, C. (2008).
Towards Self-Organizing Bureaucracies,
International Journal of Public Information Systems, 2008(1):1-24.
The goal of this paper is to contribute to eGovernment efforts, encouraging the use of self-organization as a method to improve the efficiency and adaptability of bureaucracies and similar social systems. Bureaucracies are described as networks of agents, where the main design principle is to reduce local "friction" to increase local and global "satisfaction". Following this principle, solutions are proposed for improving communication within bureaucracies, sensing public satisfaction, dynamic modification of hierarchies, and contextualization of procedures. Each of these reduces friction between agents (internal or external), increasing the efficiency of bureaucracies. Current technologies can be applied for this end. "Random agent networks" (RANs), novel computational models, are introduced to illustrate the benefits of self-organizing bureaucracies. Simulations show that only few changes are required to reach near-optimal performance, potentially adapting quickly and effectively to shifts in demand.
Gershenson, C. (2005).
Self-Organizing Traffic Lights. Complex Systems 16(1): 29-53. [preprint]
Steering traffic in cities is a very complex task, since improving efficiency involves the coordination of many actors. Traditional approaches attempt to optimize traffic lights for a particular density and configuration of traffic. The disadvantage of this lies in the fact that traffic densities and configurations change constantly. Traffic seems to be an adaptation problem rather than an optimization problem. We propose a simple and feasible alternative, in which traffic lights self-organize to improve traffic flow. We use a multi-agent simulation to study three self-organizing methods, which are able to outperform traditional rigid and adaptive methods. Using simple rules and no direct communication, traffic lights are able to self-organize and adapt to changing traffic conditions, reducing waiting times, number of stopped cars, and increasing average speeds.
Gershenson, C. (2004).
Cognitive Paradigms: Which One is the Best?
Cognitive Systems Research, 5(2):135-156, June 2004.
I discuss the suitability of different paradigms for studying cognition. I use a virtual laboratory that implements five different representative models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude that there is no "best" model, since different models are better for different things in different contexts. Using the results as an empirical philosophical aid, I note that there is no "best" approach for studying cognition, since different paradigms have all advantages and disadvantages, since they study different aspects of cognition from different contexts. This has implications for current debates on "proper" approaches for cognition: all approaches are a bit proper, but none will be "proper enough". I draw remarks on the notion of cognition abstracting from all the approaches used to study it, and propose a simple classification for different types of cognition.
Heylighen, F. and C. Gershenson (2003).
The Meaning of Self-organization in Computing.
IEEE Intelligent Systems, section Trends & Controversies - Self-organization and Information Systems, July/August 2003, pp. 72-75.
Gershenson, C. (2002b).
Philosophical Ideas on the Simulation of Social Behaviour.
Journal of Artificial Societies and Social Simulation 5(3).
In this study we consider some of the philosophical issues that should be taken into account when simulating social behaviour. Even though the ideas presented here are philosophical, they should be of interest more to researchers simulating social behaviour than to philosophers, since we try to note some problems that researchers might not put much attention to. We give notions of what could be considered a social behaviour, and mention the problems that arise if we attempt to give a sharp definition of social behaviour in a broad context. We also briefly give useful concepts and ideas of complex systems and abstraction levels (Gershenson, 2002a), since any society can be seen as a complex system. We discuss the problems that arise while modelling social behaviour, mentioning the synthetic method as a useful approach for contrasting social theories, because of the complexities of the phenomena they model. In addition, we note the importance of the study of social behaviour for the understanding of cognition. We hope that the ideas presented here motivate the interest and debate of researchers simulating social behaviour in order to pay attention to the problems mentioned in this work, and attempt to provide more suitable solutions to them than the ones proposed here.
Gershenson, C. (2007).
Towards a General Methodology for Designing Self-Organizing Systems
In Bogg, J. and R. Geyer (eds.) Complexity, Science and Society. Radcliffe Publishing, Oxford.
Gershenson, C., D. Aerts, and B. Edmonds (2007).
In Gershenson, C., D. Aerts, and B. Edmonds (Eds.). Worldviews, Science, and Us: Philosophy and Complexity. , pp. 1-4. World Scientific, Singapore.
Cools, S.-B., C. Gershenson, and B. D'Hooghe (2007).
Self-organizing traffic lights: A realistic simulation
In Prokopenko, M. (Ed.) Self-Organization: Applied Multi-Agent Systems, Chapter 3, pp. 41-49. Springer, London.
We have previously shown in an abstract simulation (Gershenson, 2005) that self-organizing traffic lights can improve greatly traffic flow for any density. In this paper, we extend these results to a realistic setting, implementing self-organizing traffic lights in an advanced traffic simulator using real data from a Brussels avenue. On average, for different traffic densities, travel waiting times are reduced by 50% compared to the current green wave method.
Heylighen, F., P. Cilliers, and C. Gershenson (2007).
Complexity and Philosophy
In Bogg, J. and R. Geyer (eds.) Complexity, Science and Society. Radcliffe Publishing, Oxford.
The science of complexity is based on a new way of thinking that
stands in sharp contrast to the philosophy underlying Newtonian science, which is
based on reductionism, determinism, and objective knowledge. This paper reviews
the historical development of this new world view, focusing on its philosophical
foundations. Determinism was challenged by quantum mechanics and chaos theory.
Systems theory replaced reductionism by a scientifically based holism. Cybernetics
and postmodern social science showed that knowledge is intrinsically subjective.
These developments are being integrated under the header of complexity science .
Its central paradigm is the multi-agent system. Agents are intrinsically subjective
and uncertain about their environment and future, but out of their local interactions,
a global organization emerges. Although different philosophers, and in particular the
postmodernists, have voiced similar ideas, the paradigm of complexity still needs to
be fully assimilated by philosophy. This will throw a new light on old philosophical
issues such as relativism, ethics and the role of the subject.
Gershenson, C. and F. Heylighen (2005).
How can we think the complex?
In Richardson, Kurt (ed.) Managing Organizational Complexity: Philosophy, Theory and Application, Chapter 3. Information Age Publishing.
This chapter does not deal with specific tools and techniques for managing complex systems, but proposes some basic concepts that help us to think and speak about complexity. We review classical thinking and its intrinsic drawbacks when dealing with complexity. We then show how complexity forces us to build models with indeterminacy and unpredictability. However, we can still deal with the problems created in this way by being adaptive, and profiting from a complex system's capability for selforganization, and the distributed intelligence this may produce.
Das, A., M. Marko, A. Probst, M. A. Porter, and C. Gershenson (2002).
Neural Net Model for Featured Word Extraction.
. In Minai, A. A. and Bar-Yam, Y. (Eds.), Unifying Themes in Complex Systems Vol. IV. pp. 353-362. Springer.
Also InterJournal of Complex Systems
Search engines perform the task of retrieving information related to the user-supplied query words. This task has two parts; one is finding 'featured words' which describe an article best and the other is finding a match among these words to user-defined search terms. There are two main independent approaches to achieve this task. The first one, using the concepts of semantics, has been implemented partially. For more details see another paper of Marko et al., 2002. The second approach is reported in this paper. It is a theoretical model based on using Neural Network (NN). Instead of using keywords or reading from the first few lines from papers/articles, the present model gives emphasis on extracting 'featured words' from an article. Obviously we propose to exclude prepositions, articles and so on, that is , English words like "of, the, are, so, therefore, " etc. from such a list. A neural model is taken with its nodes pre-assigned energies. Whenever a match is found with featured words and user-defined search words, the node is fired and jumps to a higher energy. This firing continues until the model attains a steady energy level and total energy is now calculated. Clearly, higher match will generate higher energy; so on the basis of total energy, a ranking is done to the article indicating degree of relevance to the user's interest. Another important feature of the proposed model is incorporating a semantic module to refine the search words; like finding association among search words, etc. In this manner, information retrieval can be improved markedly.
- Gershenson, C. (2007). The World as Evolving Information. In Proceedings of International Conference on Complex Systems ICCS2007.
Abstract: This paper discusses the benefits of describing the world as information, especially in the study of the evolution of life and cognition. Traditional studies encounter problems because it is difficult to describe life and cognition in terms of matter and energy, since their laws are valid only at the physical scale. However, if matter and energy, as well as life and cognition, are described in terms of information, evolution can be described consistently as information becoming more complex.
The paper presents five tentative laws of information, valid at multiple scales, which are generalizations of Darwinian, cybernetic, thermodynamic, and complexity principles. These are further used to discuss the notions of life and cognition and their evolution.
- Rodriguez, M.A., Watkins, J.H., Bollen, J., Gershenson, C. (2007). Using RDF to Model the Structure and Process of Systems. In Proceedings of International Conference on Complex Systems ICCS2007. Also LA-UR-07-5720.
Abstract: Many systems can be described in terms of networks of discrete elements and their various relationships to one another. A semantic network, or multi-relational network, is a directed labeled graph consisting of a heterogeneous set of entities connected by a heterogeneous set of relationships. Semantic networks serve as a promising general-purpose modeling substrate for complex systems. Various standardized formats and tools are now available to support practical, large-scale semantic network models. First, the Resource Description Framework (RDF) offers a standardized semantic network data model that can be further formalized by ontology modeling languages such as RDF Schema (RDFS) and the Web Ontology Language (OWL). Second, the recent introduction of highly performant triple-stores (i.e. semantic network databases) allows semantic network models on the order of $10^9$ edges to be efficiently stored and manipulated. RDF and its related technologies are currently used extensively in the domains of computer science, digital library science, and the biological sciences. This article will provide an introduction to RDF/RDFS/OWL and an examination of its suitability to model discrete element complex systems.
- Rodriguez, M.A., Steinbock, D.J., Watkins, J.H., Gershenson, C., Bollen, J., Grey, V., deGraf, B. (2007). Smartocracy: Social Networks for Collective Decision Making. 2007 Hawaii International Conference on Systems Science (HICSS).Track: Electronic Government – E-Democracy, Waikoloa, Hawaii, January 2007. Also LA-UR-06-2244.
Abstract: Smartocracy is a social software system for collective decision making. The system is composed of a social network that links individuals to those they trust to make good decisions and a decision network that links individuals to their voted-on solutions. Such networks allow a variety of algorithms to convert the link choices made by individual participants into specific decision outcomes. Simply interpreting the linkages differently (e.g. ignoring trust links, or using them to weight an individual's vote) provides a variety of outcomes fit for different decision making scenarios. This paper can discuss the Smartocracy network data structures, the suite of collective decision making algorithms currently supported, and the results of two collective decisions regarding the design of the system.
- Gershenson, C., S. A. Kauffman, and I. Shmulevich (2006). The Role of Redundancy in the Robustness of Random Boolean Networks. In Rocha, L. M., L. S. Yaeger, M. A. Bedau, D. Floreano, R. L. Goldstone, and A. Vespignani (Eds.), Artificial Life X, Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems. pp. 35-42. MIT Press.
Evolution depends on the possibility of successfully exploring fitness landscapes via mutation and recombination. With these search procedures, exploration is difficult in "rugged" fitness landscapes, where small mutations can drastically change functionalities in an organism. Random Boolean networks (RBNs), being general models, can be used to explore theories of how evolution can take place in rugged landscapes; or even change the landscapes.
In this paper, we study the effect that redundant nodes have on the robustness of RBNs. Using computer simulations, we have found that the addition of redundant nodes to RBNs increases their robustness. We conjecture that redundancy is a way of "smoothening" fitness landscapes. Therefore, redundancy can facilitate evolutionary searches. However, too much redundancy could reduce the rate of adaptation of an evolutionary process. Our results also provide supporting evidence in favour of Kauffman's conjecture (Kauffman, 2000, p.195).
- Gershenson, C. and T. Lenaerts (2006). Evolution of Complexity: Introduction to the Workshop.
Artificial Life X Workshop Proceedings. pp. 71-72.
Gershenson, C. (2004).
Updating Schemes in Random Boolean Networks: Do They Really Matter?
In Pollack, J., M. Bedau, P. Husbands, T. Ikegami, and R. A. Watson (eds.) Artificial Life IX, Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems. pp. 238-243. MIT Press.
In this paper we try to bring the debate concerning different updating schemes in RBNs to an end. We quantify for the first time loose attractors in asyncrhonous random Boolean networks (RBNs), which allows us to analyze the complexity reduction related to different updating schemes. We also report that all updating schemes yield very similar critical stability values, meaning that the "edge of chaos" does not depend on the updating scheme. After discussion, we conclude that synchonous RBNs are justifiable theoretical models of biological networks.
Gershenson, C. (2004).
Introduction to Random Boolean Networks
In Bedau, M., P. Husbands, T. Hutton, S. Kumar, and H. Suzuki (eds.) Workshop and Tutorial Proceedings, Ninth International Conference on the Simulation and Synthesis of Living Systems (ALife IX). pp. 160-173.
The goal of this tutorial is to promote interest in the study of random Boolean networks (RBNs). These can be very interesting models, since one does not have to assume any functionality or particular connectivity of the networks to study their generic properties. Like this, RBNs have been used for exploring the configurations where life could emerge. The fact that RBNs are a generalization of cellular automata makes their research a very important topic. The tutorial, intended for a broad audience, presents the state of the art in RBNs, spanning over several lines of research carried out by different groups. We focus on research done within artificial life, as we cannot exhaust the abundant research done over the decades related to RBNs.
Gershenson, C. and F. Heylighen (2004).
Protocol Requirements for Self-organizing Artifacts: Towards an Ambient Intelligence
In Proceedings of International Conference on Complex Systems ICCS2004. Also AI-Lab Memo 04-04.
We discuss which properties common-use artifacts should have to collaborate without human intervention. We conceive how devices, such as mobile phones, PDAs, and home appliances, could be seamlessly integrated to provide an "ambient intelligence" that responds to the users desires without requiring explicit programming or commands. While the hardware and software technology to build such systems already exists, yet there is no protocol to direct and give meaning to their interactions. We propose the first steps in the development of such a protocol, which would need to be adaptive, extensible, and open to the community, while promoting self-organization. We argue that devices, interacting through "game-like" moves, can learn to agree about how to communicate, with whom to cooperate, and how to delegate and coordinate specialized tasks. Like this, they may evolve distributed cognition or collective intelligence able to tackle any complex of tasks.
de la Mora-B., C.-R., C. Gershenson and García-Vega, A. (2004).
Representation Development and Behavior Modifiers
In Lemaître, C., C. A. Reyes, and J. A. González (Eds.) Advances in Artificial Intelligence IBERAMIA 2004: 9th Ibero-American Conference on AI. p. 504. LNAI 3315. Springer.
We address the problem of the development of representations by an agent and its relationship to the environment. A software agent develops a representation of its environment through a network, which captures and integrates the relationships between agent and environment through a closure mechanism. A variable behavior modifier improves the representation development. We report the preliminary results where we analyze two aspects: 1) The structural properties of the resulting representation can be used as indicators of the knowledge assimilated by the agent from the interaction with the environment. These properties can be taken as useful macrovariables from an objective point of view; and 2) The dynamics of the closure mechanism, can be seen as the internal, and therefore subjective, way used by the system to develop its representation. We are not interested only on how the mechanism functions, but also on how the representation evolves.
Gershenson, C., J. Broekaert, and D. Aerts (2003).
Contextual Random Boolean Networks
In Banzhaf, W, T. Christaller, P. Dittrich, J. T. Kim, and J. Ziegler, Advances in Artificial Life, 7th European Conference, ECAL 2003, Dortmund, Germany, pp. 615-624. LNAI 2801. Springer.
We propose the use of Deterministic Generalized Asynchronous
Random Boolean Networks (Gershenson, 2002) as models of contextual
deterministic discrete dynamical systems. We show that changes in the context
have drastic effects on the global properties of the same networks, namely the
average number of attractors and the average percentage of states in attractors.
We introduce the situation where we lack knowledge on the context as a more
realistic model for contextual dynamical systems. We notice that this makes the
network non-deterministic in a specific way, namely introducing a
non-Kolmogorovian quantum-like structure for the modelling of the network
(Aerts 1986). In this case, for example, a state of the network has the
potentiality (probability) of collapsing into different attractors, depending on
the specific form of lack of knowledge on the context.
Gershenson, C. and F. Heylighen (2003).
When Can we Call a System Self-organizing?
In Banzhaf, W, T. Christaller, P. Dittrich, J. T. Kim, and J. Ziegler, Advances in Artificial Life, 7th European Conference, ECAL 2003, Dortmund, Germany, pp. 606-614. LNAI 2801. Springer.
We do not attempt to provide yet another definition of
self-organizing systems, nor review previous definitions. We explore the
conditions necessary to describe self-organizing systems, inspired on decades of
their study, in order to understand them better. These involve the dynamics of
the system, and the purpose, boundaries, and description level chosen by an
observer. We show how, changing the level or "graining" of description, the
same system can be self-organizing or not. We also discuss common problems
we face when studying self-organizing systems. We analyse when building,
designing, and controlling artificial self-organizing systems is useful. We state
that self-organization is a way of observing systems, not a class of systems.
Gershenson, C. (2003).
Comparing Different Cognitive Paradigms with a Virtual Laboratory.
IJCAI-03: Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence,
pp. 1635-6. Morgan Kaufmann.
A public virtual laboratory is presented, where animats are controlled by mechanisms from different cognitive paradigms. A brief description of the characteristics of the laboratory and the uses it has had is given. Mainly, it has been used to contrast philosophical ideas related with the notion of cognition, and to elucidate debates on "proper" paradigms in AI and cognitive science.
Gershenson, C. (2002a). Complex
Philosophy. Proceedings of the 1 st Biennial Seminar on
Methodological & Epistemological Implications of Complexity
La Habana, Cuba.
InterJournal of Complex Systems,
We present several philosophical ideas emerging from the studies of complex systems. We make a brief introduction to the basic concepts of complex systems, for then defining "abstraction levels". These are useful for representing regularities in nature. We define absolute being (observer independent, infinite) and relative being (observer dependent, finite), and notice the differences between them. We draw issues on relative causality and absolute causality among abstraction levels. We also make reflections on determinism. We reject the search for any absolute truth (because of their infinity), and promote the idea that all comprehensible truths are relative, since they were created in finite contexts. This leads us to suggest to search the less-incompleteness of ideas and contexts instead of their truths.
Gershenson, C. (2002c).
Behaviour-based Knowledge Systems: An Epigenetic Path from
Behaviour to Knowledge.
Proceedings of the 2nd Workshop on Epigenetic Robotics.
In this paper we expose the theoretical
background underlying our current research. This
consists in the development of behaviour-based
knowledge systems, for closing the gaps between
behaviour-based and knowledge-based systems,
and also between the understandings of the
phenomena they model. We expose the
requirements and stages for developing
behaviour-based knowledge systems and discuss
their limits. We believe that these are necessary
conditions for the development of higher order
cognitive capacities, in artificial and natural
Gershenson, C. (2002e).
Classification of Random Boolean Networks
In Standish, R. K., M. A. Bedau, and H. A. Abbass (eds.)
Artificial Life VIII: Proceedings of the Eight International Conference on Artificial Life.
. pp. 1-8.
Sydney, Australia. MIT Press.
We provide the first classification of different types of Random Boolean Networks (RBNs). We study the differences of RBNs depending on the degree of synchronicity and determinism of their updating scheme. For doing so, we first define three new types of RBNs. We note some similarities and differences between different types of RBNs with the aid of a public software laboratory we developed. Particularly, we find that the point attractors are independent of the updating scheme, and that RBNs are more different depending on their determinism or non-determinism rather than depending on their synchronicity or asynchronicity. We also show a way of mapping non-synchronous deterministic RBNs into synchronous RBNs. Our results are important for justifying the use of specific types of RBNs for modelling natural phenomena.
Gershenson, C., M. A. Porter, A. Probst, M. Marko, and A. Das. (2002)
A Study on the Relevance of Information in Discriminative and
InterJournal of Complex Systems
In this paper we compare the relevance of information obtained from "discriminative" media and from "non-discriminative" media. Discriminative media are the ones which accumulate and deliver information using a heuristic selection of it. This can be made by humans, or by artificial intelligent systems, exhibiting some form of "knowledge". Non-discriminative media just collect and return information without any distinction. This can also be made by humans or by artificial systems, but there is no "knowledge" involved in the process. We ranked the words occurring in an edited electronic publication specialized in complex systems research, and we found that they approximate a modified Zipf distribution. We compared occurrences of representative words from the distribution with the occurrences in non-discriminative media. We found that a non-discriminative medium (Google) has a higher variance from of our original distribution than a semi-discriminative one (NEC Research Index), even when both appear to have their own modified Zipf distribution. We conclude that discriminative media have a higher efficiency rating, at least in the area in which they specialize, than non-discriminative media. Using the same search method, the discriminative media should deliver more relevant information. This relevancy also depends on the skills of the user, but non-discriminative media are more sensitive to poor searching skills, as there is a higher probability of delivering irrelevant information. This leads us to suggest the incorporation of intelligent classifications in different media (such as the ones suggested by the Semantic Web project), in order to increase the relevance of the delivered information.
Marko, M., M. A. Porter, A. Probst, C. Gershenson, and A. Das (2002).
Transforming the World Wide Web into a Complexity-Based Semantic
InterJournal of Complex Systems
The aim of this paper is to introduce the idea of the Semantic Web to the Complexity community and set a basic ground for a project resulting in creation of Internet-based semantic network of Complexity-related information providers. Implementation of the Semantic Web technology would be of mutual benefit to both the participants and users and will confirm self-referencing power of the community to apply the products of its own research to itself. We first explain the logic of the transition and discuss important notions associated with the Semantic Web technology. We then present a brief outline of the projects milestones.
Gershenson, C. (2001b). Comments
to Neutrosophy. In Smarandache, F. (Ed.) Proceedings of the First
International Conference on Neutrosophy, Neutrosophic Logic, Set, Probability
and Statistics, University of New Mexico. Gallup, NM. pp.
Any system based on axioms is incomplete because the axioms cannot be proven from the system, just believed. But one system can be less-incomplete than other. Neutrosophy is less-incomplete than many other systems because it contains them. But this does not mean that it is finished, and it can always be improved. The comments presented here are an attempt to make Neutrosophy even less-incomplete. I argue that less-incomplete ideas are more useful, since we cannot perceive truth or falsity or indeterminacy independently of a context, and are therefore relative. Absolute being and relative being are defined. Also the "silly theorem problem" is posed, and its partial solution described. The issues arising from the incompleteness of our contexts are presented. We also note the relativity and dependance of logic to a context. We propose "metacontextuality" as a paradigm for containing as many contexts as we can, in order to be less-incomplete and discuss some possible consequences.
González, P. P., M. Cárdenas, C. Gershenson, and J.
Integration of Computational Techniques for the Modelling of
Signal Transduction. In N.E. Mastorakis and L.A. Pecorelli-Peres
(Eds.) Advances in Systems Science: Measurement, Circuits and
Control. WSES Press.
A cell can be seen as an adaptive autonomous agent or as a society of adaptive autonomous agents, where
each can exhibit a particular behaviour depending on its cognitive capabilities. We present an intracellular
signalling model obtained by integrating several computational techniques into an agent-based paradigm. Cellulat,
the model, takes into account two essential aspects of the intracellular signalling networks: cognitive capacities
and a spatial organization. Exemplifying the functionality of the system by modelling the EGFR signalling
pathway, we discuss the methodology as well as the purposes of an intracellular signalling virtual laboratory,
presently under development.
González, P. P., C. Gershenson, M. Cárdenas, and J. Lagunez.(2000)
Intracellular Signalling Networks Using Behaviour-based Systems and the
Blackboard Architecture, Proceedings of the International Conference:
Mathematics and Computers in Biology and Chemistry (MCBC 2000), Montego
This paper proposes to model the intracellular signalling networks using a fusion of behaviour-based systems
and the blackboard architecture. In virtue of this fusion, the model developed by us, which has been named Cellulat,
allows to take account two essential aspects of the intracellular signalling networks: (1) the cognitive capabilities of
certain types of networks components and (2) the high level of spatial organization of these networks. A simple
example of modelling of Ca2+ signalling pathways using Cellulat is presented here. An intracellular signalling virtual
laboratory is being developed from Cellulat.
Gershenson, C. and P. P. González, (2000). Dynamic
Adjustment of the Motivation Degree in an Action Selection Mechanism. Proceedings of ISA '2000. Wollongong, Australia.
This paper presents a model for dynamic adjustment of the motivation degree, using a reinforcement learning approach, in an action selection mechanism previously developed by the authors. The learning takes place in the modification of a parameter of the model of combination of internal and external stimuli. Experiments that show the claimed properties are presented, using a VR simulation developed for such purposes. The importance of adaptation by learning in action selection is also discussed.
Gershenson, C., P. P. González, and J. Negrete. (2000b) Thinking
Adaptive: Towards a Behaviours Virtual Laboratory. In Meyer et. al.
(eds.) SAB 2000 Proceedings Supplement. Paris, France. ISAB press.
In this paper we name some of the advantages of virtual laboratories; and propose that a Behaviours Virtual Laboratory should be useful for both biologists and AI researchers, offering a new perspective for understanding adaptive behaviour. We present our development of a Behaviours Virtual Laboratory, which at this stage is focused in action selection, and show some experiments to illustrate the properties of our proposal, which can be accessed via Internet.
Gershenson, C., P. P. González, and J. Negrete. (2000a) Action
Selection Properties in a Software Simulated Agent, in Cairó
et. al. (Eds.) MICAI 2000: Advances in Artificial Intelligence.
Lecture Notes in Artificial Intelligence 1793, pp. 634-648. Springer-Verlag.
This article analyses the properties of the Internal Behaviour network, an action selection mechanism previously proposed by the authors, with the aid of a simulation developed for such ends. A brief review of the Internal Behaviour network is followed by the explanation of the implementation of the simulation. Then, experiments are presented and discussed analysing the properties of the action selection in the proposed model.
González, P. P., J. Negrete, A. Barreiro and C. Gershenson.(2000)
Model for Combination of External and Internal Stimuli in the Action Selection
of an Autonomous Agent, in Cairó et. al. (Eds.) MICAI 2000:
Advances in Artificial Intelligence. Lecture Notes in Artificial Intelligence
1793, pp. 621-633. Springer-Verlag.
This paper proposes a model for combination of external and internal stimuli for the action selection in an autonomous agent, based in an action selection mechanism previously proposed by the authors. This combination model includes additive and multiplicative elements, which allows to incorporate new properties, which enhance the action selection. A given parameter a, which is part of the proposed model, allows to regulate the degree of dependence of the observed external behaviour from the internal states of the entity.
Gershenson, C. (1999) Modelling
Emotions with Multidimensional Logic. Proceedings of the 18th International
Conference of the North American Fuzzy Information Processing Society (NAFIPS
'99), pp. 42-46. New York City, NY.
One of the objectives of Artificial Intelligence has
been the modelling of "human" characteristics, such as emotions, behaviour,
conscience, etc. But in such characteristics we might find certain degree of
contradiction. Previous work on modelling emotions and its problems are reviewed. A model
for emotions is proposed using multidimensional logic, which handles the degree of
contradiction that emotions might have. The model is oriented to simulate emotions in
artificial societies. The proposed solution is also generalized for actions which might
overcome contradiction (conflictive goals in agents, for example).
Gershenson, C. (1998a). Lógica
multidimensional: un modelo de lógica paraconsistente. Memorias
XI Congreso Nacional ANIEI, pp. 132-141. Xalapa, México.
La lógica multidimensional es un nuevo sistema de lógica propuesto para modelar
lógica paraconsistente. Una breve definición de lógica paraconsistente y ejemplos de
cuando es usada son dados. Se definen los principios y propiedades de la lógica
multidimensional, tales como las variables lógicas multidimensionales. Los operadores
lógicos Y, O, NO, SI... ENTONCES y SÍ Y SÓLO SI son definidos y explicados para la
lógica multidimensional. Además, se definen equivalencia, grado de contradicción, y la
proyección de la lógica multidimensional en la difusa. Esto incluye un pequeño programa
que usa lógica multidimensional.
Multidimensional logic is a new logic system proposed for modelling paraconsistent
logic. A brief definition of paraconsistent logic and examples of when it is used are
given. Multidimensional logic principles and properties, such as multidimensional logic
variables are defined. The logical operators AND, OR, NOT, IF... THEN, and IF AND ONLY IF
are defined and explained for multidimensional logic. Also, equivalence, degree of
contradiction, and the projection of multidimensional in fuzzy logic are defined. The
precedence of operators is defined, too, and the properties of the multidimensional AND
and OR are demonstrated. Furthermore, many examples are given using multidimensional
logic, pointing where it is useful, and projections of multidimensional in fuzzy logic are
defined and explained. This includes a simple program that uses multidimensional logic.
Gershenson, C. (1998b). Control
de Tráfico con Agentes: CRASH. Memorias XI Congreso Nacional
ANIEI. Xalapa, México.
El simulador CRASH (Car and Road Automated Simulation in Hyperways) usa programación
orientada a agentes para modelar el tráfico de una ciudad sin necesidad de semáforos,
tratando de demorar los vehículos el menor tiempo posible (y sin que se impacten). Esto
se hace por medio de agentes en cada automóvil y en cada cruce, y un control central.
Se hace una breve introducción al modelo de programación orientada a agentes, para
después explicar el modelo del simulador. Se describen las clases usadas en la
implementación, sus propiedades y sus relaciones, mostrando el diagrama de las clases.
Finalmente, se exponen las conclusiones que se llegaron con las simulaciones.
Gershenson, C. (1997a). El
Juego de la Vida en 3D. Memorias X Congreso Nacional ANIEI.
Primero se introduce al lector con un poco de la historia del
Juego de la Vida. Después se explican su consecuencias en dos dimensiones, y por último
se discuten sus propiedades al llevar el Juego de la Vida a una tercera dimensión, y se
muestran algunos ejemplos.
Gershenson, C. (1997b). Aplicaciones
de la Topología. Memorias X Congreso Nacional ANIEI.
En el presente trabajo se abordan algunas aplicaciones de la
Topología en la Computación, como el Juego de la Vida. Se tratan de ampliar los
conocimientos actuales sobre estas aplicaciones y sus representaciones gráficas. Se apoya
la exposición con un simulador de tiempo cíclico. También se hace una propuesta para
definir el Universo como un tiempo cíclico.
Gershenson, C. (In Press). Book Review: "Reviving the Living: Meaning Making in Living Systems". Yair Neuman.
Artificial Life, In Press.
Gershenson, C., Meza, I. V., Avilés, H. & Pineda, L.A. (2010). Film Review: “Mechanical Love”. Phie Ambo. (2009, Icarus Films).
Artificial Life 16(3):269-270
Gershenson, C. (2009). Book Review: "Reinventing the Sacred: A New View of Science, Reason, and Religion". Stuart A. Kauffman.
Artificial Life 15(4):485-487
Gershenson, C. (2008). Book Review: "Self-Organization and Emergence in Life Sciences", edited by Bernard Feltz, Marc Crommelinck and Philippe Goujon.
Artificial Life 14(2):239-240
Gershenson, C. (2007). Book Review: "Life Evolving: Molecules, Mind, and Meaning", by Christian De Duve.
Artificial Life 13(1):91-92
- Adapted for Global Coordination. Traffic Technology International, February-March 2011, p. 49.
- Paradigmas para Diseñar e Implementar Sistemas Complejos. InterFAR 1(8), April 2003. (in spanish)
Cuando los requerimientos de un sistema de cómputo crecen demasiado, es muy difícil construir sistemas con paradigmas clásicos. Un ejemplo de esto se ve con la ingeniería de software orientada a objetos, que permite el diseño y programación de sistemas mucho más complejos que con técnicas estructurales o secuenciales. Hay varias propuestas y tendencias innovadoras para diseñar, implementar, y controlar sistemas complejos en general, no sólo de software, en los cuales hay un gran número de elementos y tareas, y es difícil tener una visión completa del sistema o de la integración de sus componentes. Aquí mencionaremos algunas de ellas, las cuales pueden ser útiles en distintos casos, con referencias a trabajos que dan introducciones a cada una...
- In the mexican newspaper La Jornada (in spanish)
In Preparation or Unpublished:
- Gershenson, C. and D. A. Rosenblueth (2009). Modeling self-organizing traffic lights with elementary cellular automata. C3 Report No. 2009.06.
Abstract: There have been several highway traffic models proposed based on cellular automata. The simplest one is elementary cellular automaton rule 184. We extend this model to city traffic with cellular automata coupled at intersections using only rules 184, 252, and 136. The simplicity of the model offers a clear understanding of the main properties of city traffic and its phase transitions.
We use the proposed model to compare two methods for coordinating traffic lights: a green-wave method that tries to optimize phases according to expected flows and a self-organizing method that adapts to the current traffic conditions. The self-organizing method delivers considerable improvements over the green-wave method. For low densities, the self-organizing method promotes the formation and coordination of platoons that flow freely in four directions, i.e. with a maximum velocity and no stops. For medium densities, the method allows a constant usage of the intersections, exploiting their maximum flux capacity. For high densities, the method prevents gridlocks and promotes the formation and coordination of "free-spaces" that flow in the opposite direction of traffic.
- Gershenson, C. (2006). A General Methodology for Designing Self-Organizing Systems. Unpublished (ECCO working paper 2005-05).
Abstract: Our technologies complexify our environments. Thus, new technologies need to deal with more and more complexity. Several efforts have been made to deal with this complexity using the concept of self-organization. However, in order to promote its use and understanding, we must first have a pragmatic understanding of complexity and self-organization. This paper presents a conceptual framework for speaking about self-organizing systems. The aim is to provide a methodology useful for designing and controlling systems developed to solve complex problems. First, practical notions of complexity and self-organization are given. Then, starting from the agent metaphor, a conceptual framework is presented. This provides formal ways of speaking about "satisfaction" of elements and systems. The main premise of the methodology claims that reducing the "friction" or "interference" of interactions between elements of a system will result in a higher "satisfaction" of the system, i.e. better performance. The methodology discusses different ways in which this can be achieved. A case study on self-organizing traffic lights illustrates the ideas presented in the paper.
Das, A., G. Mayer-Kress, C. Gershenson, P. Das, M. A. Porter, and A. Probst (2004).
From Bibliometrics to Webometrics: A Case Study
Presented at International Conference on Complex Systems ICCS2004.
The field of bibliometrics is concerned with conducting quantitative analyses of documents, traditionally printed ones such as books and journal articles. For this Impact Factor (IF) is used. On the other hand, Webometrics is the application of informetric and other quantitative techniques to the study of the Web. One of the most popular measures for this is the Google PageRank (PR). We attempt in this paper to compare these indices in complexity related research field. This has become particularly important in the recent years with the advent of many web-based publication activities where there is no scope of formal print version (and hence of IF). On the other hand, many print-only publications have set up web sites and on-line versions for readers (hence, there is PR of them). Particularly, we shall discuss the relative importance of such sites with the example of the Complexity Digest (ComDig)- a weekly publication of complexity related excerpts and links with data available since 1999. For this purpose, we collected both IF (2001) and PR of 24 journals. The objective was to study whether a journal with high (low) impact factor attract more visitors to its online version and thus gather a higher (lower) PR. We plotted the (IF/PR) for each journal and could not find any visible relation between IF and PR- although expected. Apart from other factors for these, the very way PR is calculated casts some doubt. We then attempt to compare the PR of some of the most widely known complexity related web sites. We also analyzed the pattern of the visits to the ComDig site both manually and algorithmically. We thoroughly investigated the incoming links to the ComDig site, keeping in mind the fact that the incoming links (a^~votesa^) increase the PR as explained by Google. We also describe outward links, that also count as important factor in PR calculation. Finally, we discuss more content based activities that are not directed to a higher PR only and which include of incoming and outgoing links. These may lead to new evaluation system of web citation metric -different from PR.
Gershenson, C. (2003).
Phase Transitions in Random Boolean Networks with Different Updating Schemes
In this paper we study the phase transitions of different types of Random
Boolean networks. These differ in their updating scheme: synchronous,
semi-synchronous, or asynchronous, and deterministic or non-deterministic. It
has been shown that the statistical properties of Random Boolean networks
change considerable according to the updating scheme. We study with computer
simulations sensitivity to initial conditions as a measure of order/chaos. We
find that independently of their updating scheme, all network types have very
similar phase transitions, namely when the average number of connections of
nodes is between one and three. This critical value depends more on the size of
the network than on the updating scheme.
Gershenson, C. (2003).
Self-organizing Traffic Control: First Results
We developed a virtual laboratory for traffic control where agents use different strategies in order to self-organize on the road. We present our first results where we compare the performance and behaviour promoted by environmental constrains and five different simple strategies: three inspired in flocking behaviour, one selfish, and one inspired in the minority game. Experiments are presented for comparing the strategies. Different issues are discussed, such as the important role of environmental constrains and the emergence of traffic lanes.
- C. Gershenson, G. Mayer-Kress, A. Das, P. Das, and M. Marko (2003).
Time-scales, Meaning, and Availability of Information in a Global Brain.
We note the importance of time-scales, meaning, and availability of information for the emergence of novel information meta-structures at a global scale. We discuss previous work in this area and develop future perspectives. We focus on the transmission of scientific articles and the integration of traditional conferences with their virtual extensions on the Internet, their time-scales, and availability. We mention the Semantic Web as an effort for integrating meaningful information.
Gershenson, C. (2003).
On the Notion of Cognition.
We discuss philosophical issues concerning the
notion of cognition basing ourselves in experimental
results in cognitive sciences, especially in computer
simulations of cognitive systems. There have been
debates on the "proper" approach for studying
cognition, but we have realized that all approaches
can be in theory equivalent. Different approaches
model different properties of cognitive systems from
different perspectives, so we can only learn from all
of them. We also integrate ideas from several
perspectives for enhancing the notion of cognition,
such that it can co ntain other definitions of cognition
as special cases. This allows us to propose a simple
classification of different types of cognition.
- Das, A., G. Mayer-Kress, C. Gershenson, and P. Das (2003).
Conferences with Internet Web-Casting as Binding Events in a Global Brain: Example Data From Complexity Digest.
There is likeness of the Internet to human brains which has led to the metaphor of the world-wide computer network as a `Global Brain'. We consider conferences as 'binding events' in the Global Brain that can lead to metacognitive structures on a global scale. One of the critical factors for that phenomenon to happen (similar to the biological brain) are the time-scales characteristic for the information exchange. In an electronic newsletter- the Complexity Digest (ComDig) we include webcasting of audio (mp3) and video (asf) files from international conferences in the weekly ComDig issues. Here we present the time variation of the weekly rate of accesses to the conference files. From those empirical data it appears that the characteristic time-scales related to access of web-casting files is of the order of a few weeks. This is at least an order of magnitude shorter than the characteristic time-scales of peer reviewed publications and conference proceedings. We predict that this observation will have profound implications on the nature of future conference proceedings, presumably in electronic form.
- Gershenson, C. (2002).
Contextuality: A Philosophical Paradigm,
with Applications to Philosophy of Cognitive Science.
POCS Essay, COGS, University of Sussex. [pdf], [html]
Abstract: We develop on the idea that everything is related, inside, and therefore determined by a context. This stance, which at first might seem obvious, has several important consequences. This paper first presents ideas on Contextuality, for then applying them to problems in philosophy of cognitive science. Because of space limitations, for the second part we will assume that the reader is familiar with the literature of philosophy of cognitive science, but if this is not the case, it would not be a limitation for understanding the main ideas of this paper. We do not argue that Contextuality is a panaceic answer for explaining everything, but we do argue that everything is inside a context. And because this is always, we sometimes ignore it, but we believe that many problems are dissolved with a contextual approach, noticing things we ignore because of their obviousity. We first give a notion of context. We present the idea that errors are just incongruencies inside a context. We also present previous ideas of absolute being, relative being, and lessincompleteness. We state that all logics, and also truth judgements, are contextdependent, and we develop a "Context-dependant Logic". We apply ideas of Contextuality to problems in semantics, the problem of "where is the mind", and the study of consciousness.
Gershenson, C. (2002).
Where is the problem of "Where is the mind?"?
POCS Essay, COGS, University of Sussex.
We propose that the discussions about "where the mind is" depend directly on the
metaphysical preconception and definition of "mind". If we see the mind from one perspective
(individualist), it will be only in the brain, and if we see it from another (active externalist), it will
be embedded in the body and extended into the world. The "whereabouts" of the mind depends
on our <concept|definition> of mind. Therefore, we should not ask if the mind is somewhere,
but if it is somehow.
Gershenson, C. (2002).
Adaptive Development of Koncepts in Virtual Animats: Insights into the Development of Knowledge.
COGS Adaptive Systems Essay, University of Sussex.
As a part of our effort for studying the evolution and development of cognition, we present results derived from synthetic experimentations in a virtual laboratory where animats develop koncepts adaptively and ground their meaning through action. We introduce the term "koncept" to avoid confusions and ambiguity derived from the wide use of the word "concept". We present the models which our animats use for abstracting koncepts from perceptions, plastically adapt koncepts, and associate koncepts with actions. On a more philosophical vein, we suggest that knowledge is a property of a cognitive system, not an element, and therefore observer-dependent.
Gershenson, C. (2002).
Introduction to Chaos in Deterministic Systems.
Formal Computational Skills Teaching Package, COGS, University of Sussex.
The scope of this teaching package is to make a brief introduction to some notions and properties of chaotic systems. We first make a brief introduction to chaos in general and then we show some important properties of chaotic systems using the logistic map and its bifurcation diagram. We also show the universality found in "the route to chaos". The user is only required to have notions of algebra, so it is quite accessible. The formal basis of chaos theory are not covered in this introduction, but are pointed out for the reader interested in them. Therefore, this package is also useful for people who are interested in going deep into the mathematical theories, because it is a simple introduction of the terminology, and because it points out which are the original sources of information (so there is no danger in falling in the trap of "Learn Chaos in 48 hours" or "Bifurcation Diagrams for Dummies"). The included exercises are suggested for consolidating the covered topics. The on-line resources are highly recommended for extending this brief induction.
Gershenson, C. (2001).
Artificial Neural Networks for Beginners.
Formal Computational Skills Teaching Package, COGS, University of Sussex.
The scope of this teaching package is to make a brief induction to Artificial Neural Networks (ANNs) for people who have no previous knowledge of them. We first make a brief introduction to models of networks, for then describing in general terms ANNs. As an application, we explain the backpropagation algorithm, since it is widely used and many other algorithms are derived from it. The user should know algebra and the handling of functions and vectors. Differential calculus is recommendable, but not necessary. The contents of this package should be understood by people with high school education. It would be useful for people who are just curious about what are ANNs, or for people who want to become familiar with them, so when they study them more fully, they will already have clear notions of ANNs. Also, people who only want to apply the backpropagation algorithm without a detailed and formal explanation of it will find this material useful. This work should not be seen as "Nets for dummies", but of course it is not a treatise. Much of the formality is skipped for the sake of simplicity. Detailed explanations and demonstrations can be found in the referred readings. The included exercises complement the understanding of the theory. The on-line resources are highly recommended for extending this brief induction.
These works are licensed under a Creative Commons License.
In Preparation or Unpublished