CDC
2009
IEEE
13 years 9 months ago
2009
IEEE
— We consider decision-making problems in Markov decision processes where both the rewards and the transition probabilities vary in an arbitrary (e.g., nonstationary) fashion. We...
WEBDB
2010
Springer
13 years 10 months ago
2010
Springer
The transition of search engine users’ intents has been studied for a long time. The knowledge of intent transition, once discovered, can yield a better understanding of how diï...
AAMAS
2007
Springer
13 years 11 months ago
2007
Springer
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is that...
ICDAR
2009
IEEE
13 years 11 months ago
2009
IEEE
Hidden Markov Models (HMM) are probabilistic graphical models for interdependent classification. In this paper we experiment with different ways of combining the components of an ...
ICML
2006
IEEE
14 years 5 months ago
2006
IEEE
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...