Abstract. One of the most difficult problems in multiagent systems involves representing knowledge and beliefs of agents in dynamic environments. New perceptions modify an agent’...
This paper describes an investigation into the refinement of context-based human behavior models through the use of experiential learning. Specifically, a tactical agent was endow...
The central mechanism design problem is to develop incentives for agents to truthfully reveal their preferences over different outcomes, so that the system-wide outcome chosen by ...
In previous work we have introduced a principled methodology for systematically exploring the space of bidding strategies when agents participate in a significant number of simul...
When two or more agents interacting, their behaviors are not necessarily matching. Automated ways to overcome conicts in the behavior of agents can make the execution of interacti...