Genetic Algorithms for Learning Agents and Adaptive Societies

Sandeep Sen

Department of Mathematical & Computer Sciences,

University of Tulsa,

600 South College Avenue, Tulsa, OK 74104-3189.

sandip@kolkata.mcs.utulsa.edu, http://www.mcs.utulsa.edu/~sandip/

Abstract

This short tutorial will introduce you to the use of Genetic Algorithms (GAs) for designing agent behaviors and constructing sustainable agent societies. The tutorial will contain a brief introduction about the motivations and the basic mechanism for GAs, but more emphasis will be placed on the use of GAs in designing agent behaviors. In contrast to typical GA introductions emphasizing the use of GAs for optimization, the tutorial will also highlight the use of GAs as adaptive systems. For example, instances of GA applications in agent systems will include both optimizing entire agent societies and adapting individual agent behaviors to address well-known economic and social dilemmas like the Tragedy of the Commons. The tutorial will also include discussions on genetic based machine learning including the design of learning classifier systems for classification and reinforcement learning.

The following is a list of topics that will be covered in the tutorial:

Genetic Algorithm Basics --

Motivations -- Operators, Representation, Mechanisms

Genetic Based Machine Learning -- Genetic Supervised Learners, Genetic Reinforcement Learners

Designing Agents and societies with Genetic Algorithm -- Evolving agent societies, Co-evolution

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