%0 Book Section %B Unifying Themes in Complex Systems %D 2011 %T Protocol Requirements for Self-Organizing Artifacts: Towards an Ambient Intelligence %A Carlos Gershenson %A Francis Heylighen %E Minai, Ali %E Braha, Dan %E Yaneer {Bar-Yam} %X 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. %B Unifying Themes in Complex Systems %I Springer %C Berlin Heidelberg %V V %P 136-143 %G eng %U http://arxiv.org/abs/nlin.AO/0404004 %R 10.1007/978-3-642-17635-7_17 %0 Book Section %B Complexity, Science and Society %D 2007 %T Complexity and Philosophy %A Francis Heylighen %A Paul Cilliers %A Carlos Gershenson %E Jan Bogg %E Robert Geyer %B Complexity, Science and Society %I Radcliffe Publishing %C Oxford %P 117-134 %G eng %U http://arxiv.org/abs/cs.CC/0604072 %0 Book Section %B Managing Organizational Complexity: Philosophy, Theory and Application %D 2005 %T How Can We Think the Complex? %A Carlos Gershenson %A Francis Heylighen %E Kurt Richardson %X 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. %B Managing Organizational Complexity: Philosophy, Theory and Application %I Information Age Publishing %P 47–61 %G eng %U http://uk.arxiv.org/abs/nlin.AO/0402023 %& 3 %0 Journal Article %J IEEE Intelligent Systems %D 2003 %T The Meaning of Self-Organization in Computing %A Francis Heylighen %A Carlos Gershenson %B IEEE Intelligent Systems %P 72–75 %8 July/August %G eng %U http://pcp.vub.ac.be/Papers/IEEE.Self-organization.pdf %0 Conference Paper %B Advances in Artificial Life, 7th European Conference, {ECAL} 2003 {LNAI} 2801 %D 2003 %T When Can We Call a System Self-Organizing? %A Carlos Gershenson %A Francis Heylighen %E Banzhaf, W %E T. Christaller %E P. Dittrich %E J. T. Kim %E J. Ziegler %X 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. %B Advances in Artificial Life, 7th European Conference, {ECAL} 2003 {LNAI} 2801 %I Springer %C Berlin %P 606–614 %G eng %U http://arxiv.org/abs/nlin.AO/0303020