In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
Computer agents participate in many collaborative and competitive multiagent domains in which humans make decisions. For computer agents to interact successfully with people in su...
maintain awareness of its environment for a long period of time. Additionally, knowledge-intensive agents must be engineered such that their knowledge can be easily updated as envi...
nts have recently emerged as a valuable abstraction for characterizing interactions among autonomous agents at the level of their business relationships. Traditionally, interopera...
To realize large-scale socially embedded multiagent systems, this paper proposes a new system design methodology towards society-centered design. We have already developed the scen...