Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
This paper examines, by argument, the dynamics of sequences of behavioural choices made, when non-cooperative restricted-memory agents learn in partially observable stochastic gam...
A conversational method of teaching whereby the students engage each other as a key part of the learning experience achieves a higher percentage of high grades (and presumably bet...
: Growing importance of distributed data mining techniques has recently attracted attention of researchers in multiagent domain. Several agent-based application have been already c...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek, S...
As online markets for the exchange of goods and services become more common, the study of markets composed at least in part of autonomous agents has taken on increasing importance...
Christopher H. Brooks, Robert S. Gazzale, Rajarshi...