43 search results - page 5 / 9 » Learning Stochastic Finite Automata from Experts |
ESANN
2006
13 years 9 months ago
2006
Abstract. We present experimental results about learning function values (i.e. Bellman values) in stochastic dynamic programming (SDP). All results come from openDP (opendp.sourcef...
TSMC
2008
13 years 7 months ago
2008
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 tha...
ICML
2009
IEEE
14 years 2 months ago
2009
IEEE
One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
ICMLA
2004
13 years 8 months ago
2004
: The particle swarm is one of the most powerful methods for solving global optimization problems. This method is an adaptive algorithm based on social-psychological metaphor. A po...
CONCUR
2006
Springer
13 years 9 months ago
2006
Springer
In regular inference, the problem is to infer a regular language, typically represented by a deterministic finite automaton (DFA) from answers to a finite set of membership querie...