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ICTAI
1994
IEEE
15 years 1 months ago
Iterative Strengthening: An Algorithm for Generating Anytime Optimal Plans
In order to perform adequately in real-world situations, a planning system must be able to nd the \best" solution while still supporting anytime behavior. We have developed ...
Randall J. Calistri-Yeh
AUTOMATICA
2007
124views more  AUTOMATICA 2007»
14 years 9 months ago
Motion planning in uncertain environments with vision-like sensors
In this work we present a methodology for intelligent path planning in an uncertain environment using vision like sensors, i.e., sensors that allow the sensing of the environment ...
Suman Chakravorty, John L. Junkins
ICAC
2009
IEEE
14 years 7 months ago
Using distributed w-learning for multi-policy optimization in decentralized autonomic systems
Distributed W-Learning (DWL) is a reinforcement learningbased algorithm for multi-policy optimization in agent-based systems. In this poster we propose the use of DWL for decentra...
Ivana Dusparic, Vinny Cahill
AI
1999
Springer
14 years 9 months ago
Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning a
In this paper, we first discuss the meaning of physical embodiment and the complexity of the environment in the context of multi-agent learning. We then propose a vision-based rei...
Minoru Asada, Eiji Uchibe, Koh Hosoda
DSS
2002
139views more  DSS 2002»
14 years 9 months ago
CI Spider: a tool for competitive intelligence on the Web
Competitive Intelligence (CI) aims to monitor a firm's external environment for information relevant to its decision-making process. As an excellent information source, the I...
Hsinchun Chen, Michael Chau, Daniel Dajun Zeng