An original Reinforcement Learning (RL) methodology is proposed for the design of multi-agent systems. In the realistic setting of situated agents with local perception, the task o...
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
: For many complex and dynamic ubiquitous services, context-aware cooperation can be a solution. However, the way is not yet clear to make individual objects cooperate with each ot...
The deployment of multi-agent systems demands for justified confidence into their behaviour, both with respect to correct results of computations and with respect to timeliness t...
Recent scaling up of decentralized partially observable Markov decision process (DEC-POMDP) solvers towards realistic applications is mainly due to approximate methods. Of this fa...