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» Putting knowledge rich plan representations to use
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JIRS
2000
144views more  JIRS 2000»
13 years 7 months ago
An Integrated Approach of Learning, Planning, and Execution
Agents (hardware or software) that act autonomously in an environment have to be able to integrate three basic behaviors: planning, execution, and learning. This integration is man...
Ramón García-Martínez, Daniel...
AIPS
2008
13 years 10 months ago
Fast Dynamic Scheduling of Disjunctive Temporal Constraint Networks through Incremental Compilation
Autonomous systems operating in real-world environments must plan, schedule, and execute missions while robustly adapting to uncertainty and disturbance. One way to mitigate the e...
Julie A. Shah, Brian C. Williams
IJCAI
2007
13 years 9 months ago
Online Learning and Exploiting Relational Models in Reinforcement Learning
In recent years, there has been a growing interest in using rich representations such as relational languages for reinforcement learning. However, while expressive languages have ...
Tom Croonenborghs, Jan Ramon, Hendrik Blockeel, Ma...
CIKM
2005
Springer
14 years 1 months ago
A robot ontology for urban search and rescue
The goal of this Robot Ontology effort is to develop and begin to populate a neutral knowledge representation (the data structures) capturing relevant information about robots and...
Craig Schlenoff, Elena Messina
AAMAS
2000
Springer
13 years 7 months ago
Rational Coordination in Multi-Agent Environments
We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents, and present a framework that uses this paradigm t...
Piotr J. Gmytrasiewicz, Edmund H. Durfee