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January 23, Wednesday
12:00 – 13:00

Driven by the recent surge of personal mobile devices we explore the means to apply the accumulated knowledge on distributed search to realistic multi agent applications. Our work focuses on interactions where the agents are cooperative (follow the distributed interaction protocol) but have personal preferences (evaluate the outcome of a joint action differently).

The talk will provide a bird’s eye view on my Ph.D. dissertation and will begin by discussing the representation of multi agent interactions where agents are cooperative but have personal preferences. Although the standard model can capture such interactions, it limits many existing algorithms – a problem remedied by introducing asymmetric constraints.

Applying the asymmetric model to the problems at hand I will then go on to describe the implications of personal preferences on the search objective. Traditionally this objective takes one of two forms: “cooperative” - the utilitarian social welfare, for example; or “competitive” - a game theoretic stable joint action (equilibrium). I will show that both objectives are attainable within the new asymmetric distributed constraint setting but also suggest some alternative concepts which attempt to leverage the inherent agents’ cooperation in an attempt to provide a partial answer to the seemingly simple philosophical question: “what is a fair solution?”.