5 search results - page 1 / 1 » Speeding Up Planning in Markov Decision Processes via Automa... |
UAI
2008
13 years 8 months ago
2008
ICML
2006
IEEE
2006
IEEE
Automatic basis function construction for approximate dynamic programming and reinforcement learning
14 years 1 months ago
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
AAAI
1996
1996
Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations
13 years 8 months ago
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...
IJRR
2011
13 years 2 months ago
2011
Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...