Abstract— Groups of reinforcement learning agents interacting in a common environment often fail to learn optimal behaviors. Poor performance is particularly common in environmen...
Cooperative multi-agent systems are ones in which several agents attempt, through their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among t...
Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...
: This paper reports on preliminary results of an explorative study of a protocol analysis of team learning while designing using in-situ data. Two measurement-based frameworks are...
In this paper, we describe the latest version of SIBYLLE, an AAC system that permits persons suffering from severe physical disabilities to enter text with any computer applicatio...