Third International Workshop on
Guided Self-Organization (GSO-2010)
The School of Informatics & Computing (SoIC), Complex Networks and Systems Center for Research (CNetS), and Pervasive Technology Institute (PTI) at Indiana University (IU) are pleased to host the 3rd International Workshop on Guided Self-Organization, September 4-6, 2010 (Bloomington, Indiana, USA).
Research Aims and Topics
The goal of Guided Self-Organization (GSO) is to leverage the strengths of self-organization while still being able to direct the outcome of the self-organizing process. The GSO-2010 workshop will bring together invited experts and researchers in self-organizing systems, with particular emphasis on the information- and graph-theoretic foundations of GSO and the information dynamics of cognitive systems.
A number of attempts have been made to formalize aspects of GSO within information theory and dynamical systems: empowerment, information-driven evolution, robust overdesign, reinforcement-driven homeokinesis, predictive information-based homeokinesis, interactive learning, etc. What is common to many examples of GSO is the characterization of a system-environment loop (e.g., sensorimotor or perception-action loop) in information-theoretic terms. For instance, given an agent's behavior, the empowerment measures the amount of Shannon information that the agent can "inject into" its sensors through the environment, affecting future actions and future perceptions. On the other hand, maximization of the predictive information or excess entropy during a time interval enables an adaptive/evolutionary change in controllers' logic in such a way that the system becomes coordinated. Furthermore, methods relying on the use of predictive information in a sensorimotor process may produce explicit learning rules for the agent optimizing its behavior. However, the lack of a broadly applicable mathematical framework across multiple scales and contexts leaves GSO methodology incomplete. Devising such a framework and identifying common principles of guidance are the main themes of GSO workshops.
The following topics are of special interest: information-theoretic measures of complexity, graph-theoretic metrics of networks, information-driven self-organization (IDSO), applications of GSO to systems biology, computational neuroscience, cooperative and modular robotics, sensor networks, and cognitive modeling.
The program includes 3 days, each day with three keynote talks, and four regular presentations.
With great and much appreciated assistance from Tara Holbrook