63 search results - page 1 / 13 » Learning Symbolic Models of Stochastic Domains |
JAIR
2007
13 years 4 months ago
2007
In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a a new probabilistic planning rule representation to compactly ...
GECCO
2007
Springer
13 years 11 months ago
2007
Springer
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
ROBOCUP
2007
Springer
13 years 11 months ago
2007
Springer
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
JSAI
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. This paper is concerned with algorithms for the logical generalisation of probabilistic temporal models from examples. The algorithms combine logic and probabilistic mode...
CPE
2003
Springer
13 years 10 months ago
2003
Springer
We describe the main features of SmArT, a software package providing a seamless environment for the logic and probabilistic analysis of complex systems. SmArT can combine differen...