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» Observation Can Be as Effective as Action in Problem Solving
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AIPS
2004
13 years 10 months ago
A Lookahead Strategy for Heuristic Search Planning
The planning as heuristic search framework, initiated by the planners ASP from Bonet, Loerincs and Geffner, and HSP from Bonet and Geffner, lead to some of the most performant pla...
Vincent Vidal
ROBOCUP
2007
Springer
167views Robotics» more  ROBOCUP 2007»
14 years 2 months ago
Cooperative/Competitive Behavior Acquisition Based on State Value Estimation of Others
The existing reinforcement learning approaches have been suffering from the curse of dimension problem when they are applied to multiagent dynamic environments. One of the typical...
Kentarou Noma, Yasutake Takahashi, Minoru Asada
CORR
2008
Springer
90views Education» more  CORR 2008»
13 years 9 months ago
A Pseudo-Boolean Solution to the Maximum Quartet Consistency Problem
Determining the evolutionary history of a given biological data is an important task in biological sciences. Given a set of quartet topologies over a set of taxa, the Maximum Quart...
António Morgado, João P. Marques Sil...
AIPS
2000
13 years 10 months ago
Investigating the Effect of Relevance and Reachability Constraints on SAT Encodings of Planning
Currently, Graphplan and Blackbox, which converts Graphplan's plan graph into the satisfaction (SAT) problem, are two of the most successful planners. Since Graphplan gains i...
Minh Binh Do, Biplav Srivastava, Subbarao Kambhamp...
ICCV
2011
IEEE
12 years 8 months ago
Latent Low-Rank Representation for Subspace Segmentation and Feature Extraction
Low-Rank Representation (LRR) [16, 17] is an effective method for exploring the multiple subspace structures of data. Usually, the observed data matrix itself is chosen as the dic...
Guangcan Liu, Shuicheng Yan