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AI
2002
Springer
15 years 4 months ago
Multi-agent oriented constraint satisfaction
This paper presents a multi-agent oriented method for solving CSPs (Constraint Satisfaction Problems). In this method, distributed agents represent variables and a two-dimensional...
Jiming Liu, Han Jing, Yuan Yan Tang
JMLR
2008
230views more  JMLR 2008»
15 years 4 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
CP
2005
Springer
15 years 10 months ago
Boosting Distributed Constraint Satisfaction
Abstract Competition and cooperation can boost the performance of a combinatorial search process. Both can be implemented with a portfolio of algorithms which run in parallel, give...
Georg Ringwelski, Youssef Hamadi
GW
2005
Springer
119views Biometrics» more  GW 2005»
15 years 10 months ago
Dynamic Control of Captured Motions to Verify New Constraints
Simulating realistic human-like figures is still a challenging task when dynamics is involved. For example, making a virtual human jump to a given position requires to control the...
Carole Durocher, Franck Multon, Richard Kulpa
173
Voted
AMAI
2004
Springer
15 years 10 months ago
New Look-Ahead Schemes for Constraint Satisfaction
This paper presents new look-ahead schemes for backtracking search when solving constraint satisfaction problems. The look-ahead schemes compute a heuristic for value ordering and...
Kalev Kask, Rina Dechter, Vibhav Gogate