November – 2009 ^December

Distributed Constraint Satisfaction and Optimization problems provide a widely accepted framework for many multi agent tasks in AI and Operation Research. In this talk I will give a very brief introduction to Distributed Constraint Satisfaction Problems (DCSPs) and Distributed Constraint Optimization Problem (DCOPs) and mention some of the research being done in our DisCSP group. I will then move on to describe my work which involves the introduction of self interested agents into a cooperative framework. While most researchers of self interested agents apply game theoretic tools and ideas when dealing with such agents, in my work I attempt to examine the implication of selfishness on the inherently cooperative DCOP framework. My work revolves around three main aspects: the problem formulation, the notion of global optimality and the quality of a solution for each participant.

I will survey my lines of work in the fields of theoretic machine learning, automata learning, and statistical estimation. I will present some interesting recent results, and mention some open problems and topics I would like to look into further. The talk is intended to a relatively wide audience of CS graduate students, and not to machine learning professionals.