SASO 2010

Fourth IEEE International Conference on Self-Adaptive and Self-Organizing Systems

Budapest, Hungary, September 27-October 1, 2010


E-mail address of contact person as image





Parameters and Tuning Methods in Evolutionary Computing

10:00-12:00, September 27th, Monday Morning

Gusz Eiben

Speaker: Gusz Eiben (Free University Amsterdam, Amsterdam, The Netherlands)

Abstract: This tutorial elaborates on parameter tuning in the context of Evolutionary Computing (EC). However, the main issues are of a generic character, making the tutorial relevant for many other heuristic search methods that have parameters (thus: practically all of them).
The lecture considers the subject from three perspectives. First, we investigate possible definitions of evolutionary algorithm (EA) parameters and their impact on the very notion of EAs. Here we also (re)consider the "myth" of robust EA parameters. Second, we identify the core challenge of calibrating EA parameters and give an extensive overview of tuning methods, showing many examples. Third, we discuss the practical and theoretical consequences of good and fast parameter tuners on the evolutionary computing methodology of the (near) future. The tutorial is concluded with a number of concrete recommendations for EC researchers and practitioners.

Self-Organizing Applications with Polyagents (SOAPa)

14:00-17:00, September 27th, Monday Afternoon

Sven Brueckner

Speaker: Sven Brueckner (Vector Research Center, a Division of TTGSI, USA)

Authors:Sven Brueckner, Liz Downs, Van Parunak

Abstract:The success of many multi-agent systems depends on the existence of some form of organization among the individual agents that allows the system as a whole to achieve more than any single agent. In many traditional multi-agent systems, organization is imposed externally. An alternative approach is systems that organize themselves through local interactions of many simple agents in a shared environment. Self-organizing applications (SOAs) take inspiration from biology, physical world, chemistry, or social systems. Polyagents are a construct that combines the advantages of self-organizing problem solving with the need for a stronger representation of individuals and deeper reasoning. Each polyagent typically maps to a domain entity, but as the "poly" in polyagent indicates, each polyagent actually comprises multiple agents. Typically, we distinguish between one persistent agent that we call the "avatar" and a transient swarm of behavioral agents. Thus, a polyagent system performs multi-swarm reasoning. This half-day tutorial introduces the audience to engineering SOA's in general and then it puts self-organization into the context of polyagent systems. A significant portion of the tutorial is dedicated to the use of polyagents for multi-future prediction and coordination in complex, real-world domains.