221 search results - page 20 / 45 » Relational Reinforcement Learning for Agents in Worlds with ... |
ICMLA
2004
13 years 9 months ago
2004
In some environments, a learning agent must learn to balance competing objectives. For example, a Q-learner agent may need to learn which choices expose the agent to risk and whic...
AAAI
2000
13 years 9 months ago
2000
We have constructed ADVISOR, a two-agent machine learning architecture for intelligent tutoring systems (ITS). The purpose of this architecture is to centralize the reasoning of a...
AAAI
1998
13 years 9 months ago
1998
The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create a...
ISMIS
2009
Springer
14 years 2 months ago
2009
Springer
Many clustering methods are based on flat descriptions, while data regarding real-world domains include heterogeneous objects related to each other in multiple ways. For instance,...
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...