5 search results - page 1 / 1 » Speeding Up Planning in Markov Decision Processes via Automa... |
UAI
2008
13 years 6 months ago
2008
ICML
2006
IEEE
2006
IEEE
Automatic basis function construction for approximate dynamic programming and reinforcement learning
13 years 10 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 6 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 5 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
12 years 11 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...