495 search results - page 83 / 99 » Constructing States for Reinforcement Learning |
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
— The semantics of neural networks can be analyzed mathematically as a distributed system of knowledge and as systems of possible worlds expressed in the knowledge. Learning in a...
IJAR
2008
13 years 7 months ago
2008
When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit observations, as they are read from a database, we call the process stru...
ATAL
2010
Springer
13 years 8 months ago
2010
Springer
Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
SARA
2005
Springer
14 years 1 months ago
2005
Springer
Sets of features in Markov decision processes can play a critical role ximately representing value and in abstracting the state space. Selection of features is crucial to the succe...