4446 search results - page 3 / 890 » Learning Observer Agents |
ICML
1994
IEEE
13 years 11 months ago
1994
IEEE
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
COLT
2007
Springer
14 years 1 months ago
2007
Springer
In the standard model of observational learning, n agents sequentially decide between two alternatives a or b, one of which is objectively superior. Their choice is based on a stoc...
ICCBR
2010
Springer
13 years 11 months ago
2010
Springer
In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...
IDEAL
2000
Springer
13 years 11 months ago
2000
Springer
Observational learning algorithm is an ensemble algorithm where each network is initially trained with a bootstrapped data set and virtual data are generated from the ensemble for ...
ICML
1999
IEEE
13 years 11 months ago
1999
IEEE
Developing automated agents that intelligently perform complex real world tasks is time consuming and expensive. The most expensive part of developing these intelligent task perfo...