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» Limits and Possibilities of BDDs in State Space Search
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CEC
2009
IEEE
14 years 2 months ago
Memory-enhanced Evolutionary Robotics: The Echo State Network Approach
— Interested in Evolutionary Robotics, this paper focuses on the acquisition and exploitation of memory skills. The targeted task is a well-studied benchmark problem, the Tolman ...
Cédric Hartland, Nicolas Bredeche, Mich&egr...
SPIN
2004
Springer
14 years 3 months ago
Explicit State Model Checking with Hopper
The Murϕ-based Hopper tool is a general purpose explicit model checker. Hopper leverages Murϕ’s class structure to implement new algorithms. Hopper differs from Murϕ in that i...
Michael Jones, Eric Mercer
AAAI
2000
13 years 11 months ago
Localizing Search in Reinforcement Learning
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
Gregory Z. Grudic, Lyle H. Ungar
ICIP
2007
IEEE
14 years 11 months ago
Epipolar Spaces for Active Binocular Vision Systems
Depth recovery for active binocular vision systems is simplified if the camera geometry is known and corresponding points can be restricted to epipolar lines. Unfortunately, compu...
James Monaco, Alan C. Bovik, Lawrence K. Cormack
TC
1998
13 years 9 months ago
Abstraction Techniques for Validation Coverage Analysis and Test Generation
ion Techniques for Validation Coverage Analysis and Test Generation Dinos Moundanos, Jacob A. Abraham, Fellow, IEEE, and Yatin V. Hoskote —The enormous state spaces which must be...
Dinos Moundanos, Jacob A. Abraham, Yatin Vasant Ho...