We propose an online algorithm for planning under uncertainty in multi-agent settings modeled as DEC-POMDPs. The algorithm helps overcome the high computational complexity of solv...
: This paper is dedicated to the issue of structural performance of multi-agent platforms. Due to the wide range of all available architectures, we have concentrated only on Java R...
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Abstract. This is a position paper reporting the motivations, the starting point and the guidelines that characterise the MERCURIO5 project proposal, submitted to MIUR PRIN 20096 ....
In Open Multi-Agent Systems (OMAS), deciding with whom to interact is a particularly difficult task for an agent, as repeated interactions with the same agents are scarce, and rep...