We develop a model of normative systems in which agents are assumed to have multiple goals of increasing priority, and investigate the computational complexity and game theoretic ...
In this paper we combine existing work in the area of social laws with a framework for reasoning about knowledge in multi-agent systems. The unifying framework in which this is do...
Wiebe van der Hoek, Mark Roberts, Michael Wooldrid...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Most former studies of Distributed Constraint Optimization Problems (DisCOPs) search considered only complete search algorithms, which are practical only for relatively small prob...
anguage (Event B), hence staying at the same abstraction level. Thus we take advantage from the Event B method: (i) it is possible to use the method during the whole development pr...