Many applications of CSPs require partial solutions to be found before all the information about the problem is available. We examine the case where the future is partially known, and where it is important to make decisions in the present that will be robust in the light of future events. We introduce the branching CSP to model these situations, incorporating some elements of decision theory, a...

We introduce a new branch and bound algorithm for the maximum common subgraph and maximum common connected subgraph problems which is based around vertex labelling and partitioning. Our method in some ways resembles a traditional constraint programming approach, but uses a novel compact domain store and supporting inference algorithms which dramatically reduce the memory and computation require...

The block-packing problem has applications in chip design, factory layout, container shipment optimization, scheduling and other areas. It has been actively studied in the last 20 years, but symmetry in packings has been neglected. Our work deals with symmetry in several formulations of block-packing, including optimization and constraint-satisfaction variants, as well as slicing and non-slicin...

The weighted CSP framework is a soft constraint framework with a wide range of applications. Most current state-of-the-art complete solvers can be described as a basic depth-first branch and bound search that maintain some form of arc consistency during the search. In this paper we introduce a new stronger form of arc consistency, that we call existential directional arc consistency and we prov...

This work’ integrates three related AI search techniques constraint satisfaction, branch-and-bound and solution synthesis and applies the result to semantic processing in natural language (NL). We summarize the approach as “Hunter-Gatherer:” o branch-and-bound and constraint satisfaction allow us to “hunt down” non-optimal and impossible solutions and prune them from the search space. e solutio...

Consistency techniques proved to be an efficient method for reducing the search space of CSP. Several consistency techniques were proposed for soft constraint frameworks too. In this paper, we propose a full arc consistency (FAC) for weighted CSP (WCSP) and an algorithm for enforcing FAC and maintaining it during Branch & Bound search. We also define the transformation of constraint hierarchies...

The ‘Progressive Party Problem’ [9] has long been considered a problem intractable for branch-and-bound mixed integer solvers. Quite impressive results have been reported with constraint programming systems for this problem. As a result the problem has become a standard example in texts on constraint programming. Fortunately, there has been progress in the mixed integer programming arena: we ca...

The lexicographically-ordered CSP (“lexicographic CSP” or “LO-CSP” for short) combines a simple representation of preferences with the feasibility constraints of ordinary CSPs. Preferences are defined by a total ordering across all assignments, such that a change in assignment to a given variable is more important than any change in assignment to any less important variable. In this paper, we s...

We propose a new method for solving Valued Constraint Satisfaction Problems based both on backtracking techniques branch and bound and the notion of tree-decomposition of valued constraint networks. This mixed method aims to benefit from the practical efficiency of enumerative algorithms while providing a warranty of a bounded time complexity. Indeed the time complexity of our method is O(d ++1...

We propose a new algorithm for solving Distributed Constraint Optimization Problems (DCOPs). Our algorithm, called DyBop, is based on branch and bound search with dynamic ordering of agents. A distinctive feature of this algorithm is that it uses the concept of valued nogood. Combining lower bounds on inferred valued nogoods computed cooperatively helps pruning dynamically unfeasible sub-proble...