Dealing with Risk Aversion in Multiagent Systems: An Insurance Policy
Speaker: Greg Hines
In much of the literature in multiagent systems, researchers assume
(either implicitly or explicitly) that the agents are risk-neutral.
However, this assumption is not always warranted in that agents can be
risk-averse. Understanding the implications of risk-aversion in
multiagent systems and ways of mitigating it are interesting open
problems which may have ramifications on how we design mechanisms and
algorithms. In this talk I will present an insurance mechanism that can
be applied to multiagent settings where the agents are self-interested
and risk-averse. I will discuss experimental results which illustrate
the benefit of the insurance mechanism, as well as describe what types
of multiagent interactions most benefit from it.