AIPS
2009
14 years 8 months ago
2009
When modeling real-world decision-theoretic planning problems in the Markov decision process (MDP) framework, it is often impossible to obtain a completely accurate estimate of tr...
UAI
2000
14 years 8 months ago
2000
We propose a new approach to the problem of searching a space of policies for a Markov decision process (MDP) or a partially observable Markov decision process (POMDP), given a mo...
AAAI
2000
14 years 8 months ago
2000
We propose a frameworkfor robot programming which allows the seamless integration of explicit agent programming with decision-theoretic planning. Specifically, the DTGolog model a...
NIPS
2004
14 years 9 months ago
2004
We introduce a new algorithm based on linear programming that approximates the differential value function of an average-cost Markov decision process via a linear combination of p...
AIPS
2006
14 years 9 months ago
2006
This paper presents an adaptation of the standard quantum search technique to enable application within Dynamic Programming, in order to optimise a Markov Decision Process. This i...
AAAI
2006
14 years 9 months ago
2006
We examine the problem of Transfer in Reinforcement Learning and present a method to utilize knowledge acquired in one Markov Decision Process (MDP) to bootstrap learning in a mor...
ATAL
2008
Springer
14 years 9 months ago
2008
Springer
Meta-level control manages the allocation of limited resources to deliberative actions. This paper discusses efforts in adding meta-level control capabilities to a Markov Decision...
EXACT
2008
14 years 9 months ago
2008
An important requirement for intelligent assistants is to have an explanation generation mechanism, so that the trainee has a better understanding of the recommended actions and ca...
ICML
1994
IEEE
14 years 11 months ago
1994
IEEE
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
PRICAI
2000
Springer
14 years 11 months ago
2000
Springer
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...