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...
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...
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...
We consider random instances of constraint satisfaction problems where each variable has domain size O(1), each constraint is on O(1) variables and the constraints are chosen from...
We study the runtime distributions of backtrack procedures for propositional satisfiability and constraint satisfaction. Such procedures often exhibit a large variability in perfor...
Carla P. Gomes, Bart Selman, Nuno Crato, Henry A. ...