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AAAI
2008
13 years 11 months ago
Learning and Inference with Constraints
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...
CSCLP
2008
Springer
13 years 10 months ago
From Rules to Constraint Programs with the Rules2CP Modelling Language
In this paper, we present a rule-based modelling language for constraint programming, called Rules2CP. Unlike other modelling languages, Rules2CP adopts a single knowledge represen...
François Fages, Julien Martin
IJCAI
2007
13 years 10 months ago
On Modeling Multiagent Task Scheduling as a Distributed Constraint Optimization Problem
This paper investigates how to represent and solve multiagent task scheduling as a Distributed Constraint Optimization Problem (DCOP). Recently multiagent researchers have adopted...
Evan Sultanik, Pragnesh Jay Modi, William C. Regli
AAAI
1994
13 years 10 months ago
Improving Repair-Based Constraint Satisfaction Methods by Value Propagation
A constraint satisfaction problem (CSP) is a problem to find an assignment that satisfies given constraints. An interesting approach to CSP is a repair-based method that first gen...
Nobuhiro Yugami, Yuiko Ohta, Hirotaka Hara
CORR
2010
Springer
173views Education» more  CORR 2010»
13 years 9 months ago
Automatic Modular Abstractions for Template Numerical Constraints
c Modular Abstractions for Template Numerical Constraints David Monniaux May 26, 2010 We propose a method for automatically generating abstract transformstatic analysis by abstrac...
David Monniaux