Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
This article describes our participation at the Domain-Specific track. We used the Xtrieval framework [2], [3] for the preparation and execution of the experiments. The translatio...
Social norms enable coordination in multiagent systems by constraining agent behaviour in order to achieve a social objective. Automating the design of social norms has been shown...
George Christelis, Michael Rovatsos, Ronald P. A. ...
This paper discusses the use of networks-on-chip (NoCs) consisting of multiple voltage-frequency islands to cope with power consumption, clock distribution and parameter variation...