We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
Methods for solving Distributed Constraint Optimization Problems (DCOP) have emerged as key techniques for distributed reasoning. Yet, their application faces significant hurdles...
We investigate the computational complexity of reasoning about multi-agent systems using the cooperation logic ATL of Alur, Henzinger, and Kupferman. It is known that satisfiabili...
Wiebe van der Hoek, Alessio Lomuscio, Michael Wool...
The most important and interesting of the computing challenges we are facing are those that involve the problems and opportunities afforded by massive decentralization and disinte...