Sciweavers

1138 search results - page 63 / 228
» Feature Markov Decision Processes
Sort
View
ALT
2006
Springer
15 years 9 months ago
Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning
Abstract. Recently, some non-regular subclasses of context-free grammars have been found to be efficiently learnable from positive data. In order to use these efficient algorithms ...
Takeshi Shibata, Ryo Yoshinaka, Takashi Chikayama
81
Voted
ICML
2006
IEEE
16 years 1 months ago
Qualitative reinforcement learning
When the transition probabilities and rewards of a Markov Decision Process are specified exactly, the problem can be solved without any interaction with the environment. When no s...
Arkady Epshteyn, Gerald DeJong
100
Voted
ICML
2006
IEEE
16 years 1 months ago
An intrinsic reward mechanism for efficient exploration
How should a reinforcement learning agent act if its sole purpose is to efficiently learn an optimal policy for later use? In other words, how should it explore, to be able to exp...
Özgür Simsek, Andrew G. Barto
92
Voted
ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
15 years 7 months ago
A formal framework for robot learning and control under model uncertainty
— While the Partially Observable Markov Decision Process (POMDP) provides a formal framework for the problem of robot control under uncertainty, it typically assumes a known and ...
Robin Jaulmes, Joelle Pineau, Doina Precup
103
Voted
AAAI
2007
15 years 3 months ago
Situated Conversational Agents
A Situated Conversational Agent (SCA) is an agent that engages in dialog about the context within which it is embedded. Situated dialog is characterized by its deep connection to ...
William Thompson