author={Patrick Prosser},
  journal={Computational Intelligence},
  • Patrick Prosser
  • Published 1 August 1993
  • Computer Science
  • Computational Intelligence
It might be said that there are five basic tree search algorithms for the constraint satisfaction problem (csp), namely, naive backtracking (BT), backjumping (BJ), conflict‐directed backjumping (CBJ), backmarking (BM), and forward checking (FC). In broad terms, BT, BJ, and CBJ describe different styles of backward move (backtracking), whereas BT, BM, and FC describe different styles of forward move (labeling of variables). This paper presents an approach that allows base algorithms to be… 

Retroactive Ordering for Dynamic Backtracking

The experimental results presented in this paper show an advantage of the new class of heuristics and algorithms over standard DBT and over CBJ over standard Conflict-directed Backjumping.

Constraint-Directed Backtracking

  • W. PangS. Goodwin
  • Computer Science
    Australian Joint Conference on Artificial Intelligence
  • 1997
We propose a new backtracking algorithm called constraint- directed backtracking (CDBT) for solving general constraint-satisfaction problems (CSPs). CDBT searches for an assignment to variables in a

Dynamic variable ordering in graph based backjumping algorithms for csps

The implementation of Dynamic Variable Ordering (DVO) heuristic of instantiating next the variable with the Minimum Remaining Values (MRV) in the graph based backjumping algorithms is investigated and shown that it results in a significant improvements in many of them.

Conflict-Directed Backjumping Revisited

This paper shows that there exists a "perfect" dynamic variable ordering such that CBJ becomes redundant, and empirically shows that adding CBJ to a backtracking algorithm that maintains generalized arc consistency (GAC), an algorithm that is referred to as GAC-CBJ, can still provide orders of magnitude speedups.

Reasoning from last conflict(s) in constraint programming

Conflict Directed Backjumping for Max-CSPs

The present study introduces Conflict-directed Backjumping (CBJ) for Branch and Bound algorithms and shows that the performance of all algorithms is improved both in the number of assignments and in the time for completion.

Extending Forward Checking

This paper presents a general approach to extending constraint propagating algorithms, especially forward checking, and provides a simple yet flexible mechanism for pruning domain values, and shows that with this in place it becomes easy to utilize new mechanisms for detecting inconsistent values during search.

Failure-Driven Refinement Search with Local Repair-Based Heuristics for Constraint Satisfaction Problems

A complete’ hybrid method called failure driven search control with min-conflict repair (FDB-MC) for solving constraint satisfaction problems and can be proved to find an optimal solution.

Dynamic Backtracking for Dynamic Constraint Satisfaction Problems

An extension of the Dynamic Backtracking algorithm which provides the user with explanations in case of inconsistency and allows dynamic CSPs to be dealt with very eeciently is proposed.



Experimental Evaluation of Preprocessing Techniques in Constraint Satisfaction Problems

The results show that directional arc-consistency, a scheme which embodies the simplest form of constraint recording, outperforms all other preprocessing techniques and the results of the second part of the experiment suggest that the best variable ordering is achieved by the fixed max-cardinality search order.

Consistency in Networks of Relations

A Sufficient Condition for Backtrack-Free Search

A relationship involving the structure of the constraints is described which characterizes to some degree the extreme case of mimmum backtracking and a concept called "width," which may provide some guidance in the representation of constraint satisfaction problems and the order in which they are searched.

Network-based heuristics for constraint satisfaction problems

This paper identifies classes of problems that lend themselves to easy solutions, and develops algorithms that solve these problems optimally by generating heuristic advice to guide the order of value assignments based on both the sparseness found in the constraint network and the simplicity of tree-structured CSPs.

A General Backtrack Algorithm That Eliminates Most Redundant Tests

A faster algorithm functionally equivalent to the classical backtrack algorithm for assignment p rob lems, of which the Eight Queens puzzle is an example, is def ined below in general form by recursive SAIL p rocedu re BKMARK.

Enhancement Schemes for Constraint Processing: Backjumping, Learning, and Cutset Decomposition

Algorithms for Constraint-Satisfaction Problems: A Survey

A large number of problems in AI and other areas of computer science can be viewed as special cases of the constraint-satisfaction problem, and a number of different approaches have been developed for solving them.

to Constraint Satisfaction

A constraint satisfaction problem (csp) de ned over a constraint network consists of a nite set of variables, each associated with a domain of values, and a set of constraints. A solution is an