148 search results - page 20 / 30 » Reinforcement Learning for P2P Searching |
ICML
1994
IEEE
13 years 11 months ago
1994
IEEE
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
ICML
2001
IEEE
14 years 8 months ago
2001
IEEE
Direct policy search is a practical way to solve reinforcement learning problems involving continuous state and action spaces. The goal becomes finding policy parameters that maxi...
AIPS
2008
13 years 10 months ago
2008
Planning problems are often formulated as heuristic search. The choice of the heuristic function plays a significant role in the performance of planning systems, but a good heuris...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
We present a reinforcement learning architecture, Dyna-2, that encompasses both samplebased learning and sample-based search, and that generalises across states during both learni...
EWCBR
2008
Springer
13 years 9 months ago
2008
Springer
To meet time constraints, a CBR system must control the time spent searching in the case base for a solution. In this paper, we presents the results of a case study comparing the p...