Policy Reuse is a reinforcement learning technique that efficiently learns a new policy by using past similar learned policies. The Policy Reuse learner improves its exploration b...
Purpose Knowledge management for space exploration is part of a multi-generational effort. Each mission builds on knowledge from prior missions, and learning is the first step in ...
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
Ad-hoc Grids are highly heterogeneous and dynamic networks, one of the main challenges of resource allocation in such environments is to find mechanisms which do not rely on the ...
As mobile phone becomes popular in the society and many people can afford the cost, the demand of mobility is extended to teaching and learning purposes. One recent and significan...