178 search results - page 11 / 36 » Probabilistic policy reuse in a reinforcement learning agent |
ICML
2002
IEEE
14 years 9 months ago
2002
IEEE
We present several new algorithms for multiagent reinforcement learning. A common feature of these algorithms is a parameterized, structured representation of a policy or value fu...
ATAL
2010
Springer
13 years 9 months ago
2010
Springer
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...
IJCAI
2007
13 years 10 months ago
2007
The options framework provides a method for reinforcement learning agents to build new high-level skills. However, since options are usually learned in the same state space as the...
AAAI
1996
13 years 10 months ago
1996
Procedural representations of control policies have two advantages when facing the scale-up problem in learning tasks. First they are implicit, with potential for inductive genera...
AAAI
2010
13 years 10 months ago
2010
Due to the non-stationary environment, learning in multi-agent systems is a challenging problem. This paper first introduces a new gradient-based learning algorithm, augmenting th...