We had three papers accepted to this year's Autonomous Agents and Multiagent Systems Conference. The first one will get a full presentation and the other two will be presented as posters.
- Benito Mendoza and José M. Vidal. Bidding
Algorithms for a Distributed Combinatorial Auction. In
Proceedings of the Autonomous Agents and Multi-Agent Systems
Benito builds on my previous effort to design a bidding algorithm for the PAUSE auction by providing a much faster bidding algorithm. The PAUSE auction is a combinatorial auction in which the bidders themselves solve the winner determination problem in order to win. They do so because that is the only way to win! Thus, the auction provides a simple way to distribute the computation among the agents. Our algorithms implement the myopically-optimal strategy for the agents in such an auction which is to calculate a new winning bidsest but only if in that bidset they would get more utility than they get from the currently winning bidset. In other words, if I don't get any more utility from a new bidset then I won't bother to calculate one (of course, some else might think differently.
- Hrishikesh J. Goradia and José M. Vidal. An Equal Excess
Negotiation Algorithm for Coalition Formation. In Proceedings
of the Autonomous Agents and Multi-Agent Systems Conference,
Hrishikesh's attacks a problem similar to the one solved by the PAUSE auction but in this case it is the goods (items for sale) which negotiate to find the best allocation. This maps better to service-oriented architecture scenarios where various service providers are trying to sell their services but the buyers only want bundles. For example, you might only want a shipping service if you can also buy the book you want, both for less than $10. We present an algorithm based on Equal Excess theory which is an old solution concept to the negotiation problem (aka characteristic form game).
- Hong Jiang, José M. Vidal, and Michael N. Huhns. EBDI: An
Architecture for Emotional Agents. In Proceedings of the
Autonomous Agents and Multi-Agent Systems Conference, 2007.
Hong is studying the problem of how to incorporate established emotional models from psychology into autonomous agents, namely BDI agents. This paper presents a first try at an architecture that will blend these two. The goal is to develop agents that behave like humans—with all the irrationality that that implies. We speculate that as agents start to take over more of our tasks, such as buying/bargaining with others, that users will be angry if their agents do not behave like they would, even if such a behaviors would be deemed irrational by a standard utility-maximizing model.