Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Distributed Constraint Optimization (DCOP) is a general framework that can model complex problems in multi-agent systems. Several current algorithms that solve general DCOP instan...
We take institutions seriously as both a rational response to dilemmas in which agents found themselves and a frame to which later rational agents adapted their behaviour in turn....
Games may be represented in many different ways, and different representations of games affect the complexity of problems associated with games, such as finding a Nash equilib...
The aggregation of conflicting preferences is a key issue in multiagent systems. Due to its universality, voting has a central role among preference aggregation mechanisms. Votin...