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AAAI
1994
15 years 2 months ago
Solution Reuse in Dynamic Constraint Satisfaction Problems
Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environ...
Gérard Verfaillie, Thomas Schiex
CPAIOR
2010
Springer
14 years 11 months ago
Lazy Clause Generation: Combining the Power of SAT and CP (and MIP?) Solving
Finite domain propagation solving, the basis of constraint programming (CP) solvers, allows building very high-level models of problems, and using highly specific inference encapsu...
Peter J. Stuckey
FLAIRS
2006
15 years 2 months ago
Full Restart Speeds Learning
Because many real-world problems can be represented and solved as constraint satisfaction problems, the development of effective, efficient constraint solvers is important. A solv...
Smiljana Petrovic, Susan L. Epstein
AI
2002
Springer
15 years 1 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
ICS
2003
Tsinghua U.
15 years 6 months ago
PowerHerd: dynamic satisfaction of peak power constraints in interconnection networks
Power consumption is a critical issue in interconnection network design, driven by power-related design constraints, such as thermal and power delivery design. Usually, off-line w...
Li Shang, Li-Shiuan Peh, Niraj K. Jha