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» Using Learning in a Control Agent
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SAGA
2009
Springer
15 years 9 months ago
Bounds for Multistage Stochastic Programs Using Supervised Learning Strategies
We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible dec...
Boris Defourny, Damien Ernst, Louis Wehenkel
AI
2007
Springer
15 years 2 months ago
Learning action models from plan examples using weighted MAX-SAT
AI planning requires the definition of action models using a formal action and plan description language, such as the standard Planning Domain Definition Language (PDDL), as inp...
Qiang Yang, Kangheng Wu, Yunfei Jiang
ICONIP
2004
15 years 3 months ago
Neural-Evolutionary Learning in a Bounded Rationality Scenario
Abstract. This paper presents a neural-evolutionary framework for the simulation of market models in a bounded rationality scenario. Each agent involved in the scenario make use of...
Ricardo Matsumura de Araújo, Luís C....
CA
2002
IEEE
15 years 7 months ago
Representing and Parameterizing Agent Behaviors
The last few years have seen great maturation in understanding how to use computer graphics technology to portray 3D embodied characters or virtual humans. Unlike the off-line, an...
Norman I. Badler, Jan M. Allbeck, Liwei Zhao, Meer...
123
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CW
2005
IEEE
15 years 8 months ago
Agent Models for Dynamic 3D Virtual Worlds
Agents are systems capable of perceiving their environment through sensors, reasoning about their sensory input using some characteristic reasoning process and acting in their env...
Mary Lou Maher, Kathryn Elizabeth Merrick