This paper concerns the task of removing redundant information from a given knowledge base, and restructuring it in the form of a tree, so as to admit efficient problem solving ro...
Inference tasks in Markov random fields (MRFs) are closely related to the constraint satisfaction problem (CSP) and its soft generalizations. In particular, MAP inference in MRF i...
Many optimization techniques, including several targeted specifically at embedded systems, depend on the ability to calculate the number of elements that satisfy certain conditio...
Sven Verdoolaege, Rachid Seghir, Kristof Beyls, Vi...
Non-binary constraint satisfaction problems (CSPs) can be solved in two different ways. We can either translate the problem into an equivalent binary one and solve it using well-e...
We present a new polynomial-space algorithm, called Adopt, for distributed constraint optimization (DCOP). DCOP is able to model a large class of collaboration problems in multi-a...
Pragnesh Jay Modi, Wei-Min Shen, Milind Tambe, Mak...