We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
Current trends in model construction in the field of agentbased computational economics base behavior of agents on either game theoretic procedures (e.g. belief learning, fictit...
This paper presents a framework for describing the spatial distribution and the global frequency of agents who play the spatial prisoner’s dilemma with coalition formation. The ...
This paper addresses the problem of automated advice provision in settings that involve repeated interactions between people and computer agents. This problem arises in many real ...
Interactive narrative allows the user to play a role in a story and interact with other characters controlled by the system. Directorial control is a procedure for dynamically tun...