Multiagent reinforcement learning problems are especially difficult because of their dynamism and the size of joint state space. In this paper a new benchmark problem is proposed, ...
Wepresent our approach to agent modelingfor communication, and compareit to an approach to agent modelingfor other types of action. The comparisonshould be instructive since both ...
Modeling dynamical systems composed of aggregations of primitive proteins is critical to the field of astrobiological science, which studies early evolutionary structures dealing ...
The Marchitecture is a cognitive architecture for autonomous development of representations. The goals of The Marchitecture are domain independence, operating in the absence of kn...
Situated Multi Agent System models are characterized by the representation and exploitation of spatial information related to agents, the environment they inhabit and their positi...