1235 search results - page 77 / 247 » Reinforcement learning in a nutshell |
ML
2002
ACM
14 years 10 months ago
2002
ACM
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
ICONIP
2009
14 years 8 months ago
2009
Reinforcement learning induces non-stationarity at several levels. Adaptation to non-stationary environments is of course a desired feature of a fair RL algorithm. Yet, even if the...
111
click to vote
CORR
2012
Springer
13 years 6 months ago
2012
Springer
Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, lar...
140
click to vote
AGENTS
2001
Springer
15 years 3 months ago
2001
Springer
In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
AGENTS
1999
Springer
15 years 2 months ago
1999
Springer
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...