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ICDCS
2000
IEEE
13 years 9 months ago
The Effect of Nogood Learning in Distributed Constraint Satisfaction
We present resolvent-based learning as a new nogood learning method for a distributed constraint satisfaction algorithm. This method is based on a look-back technique in constrain...
Makoto Yokoo, Katsutoshi Hirayama
ICCD
2007
IEEE
183views Hardware» more  ICCD 2007»
14 years 2 months ago
Constraint satisfaction in incremental placement with application to performance optimization under power constraints
We present new techniques for explicit constraint satisfaction in the incremental placement process. Our algorithm employs a Lagrangian Relaxation (LR) type approach in the analyt...
Huan Ren, Shantanu Dutt
AAAI
2006
13 years 6 months ago
A New Approach to Distributed Task Assignment using Lagrangian Decomposition and Distributed Constraint Satisfaction
We present a new formulation of distributed task assignment, called Generalized Mutual Assignment Problem (GMAP), which is derived from an NP-hard combinatorial optimization probl...
Katsutoshi Hirayama
ATAL
2001
Springer
13 years 9 months ago
Dynamic Distributed Resource Allocation: A Distributed Constraint Satisfaction Approach
Abstract. In distributed resource allocation a set of agents must assign their resources to a set of tasks. This problem arises in many real-world domains such as distributed senso...
Pragnesh Jay Modi, Hyuckchul Jung, Milind Tambe, W...