Arc-consistency in dynamic CSPs is no more prohibitive

Debruyne, Romuald

doi:10.1109/tai.1996.560467

Cited by 16 publications

(13 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2. justification-based methods. See for example [5,6,19,29,67,68]. Based on a TMSlike (truth maintenance system) approach [26], they use the justification that has been recorded with each implied constraint c 0 to determine whether c 0 becomes questionable.…”

Section: Reasoning Reuse Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

Constraint Solving in Uncertain and Dynamic Environments: A Survey

Verfaillie

Jussien²

2005

Constraints

View full text Add to dashboard Cite

show abstract

Section: Reasoning Reuse Techniquesmentioning

confidence: 99%

“…A synthesis of some of these methods in the context of arc consistency enforcing for dynamic CSP can be found in [19] (short version) or in French in [18] (longer version).…”

Section: Reasoning Reuse Techniquesmentioning

confidence: 99%

Constraint Solving in Uncertain and Dynamic Environments: A Survey

Verfaillie

Jussien²

2005

Constraints

View full text Add to dashboard Cite

show abstract

“…The AC-4 algorithm is not the most efficient algorithm for arcconsistency enforcement, neither in a centralized (Wallace, 1993), a distributed (Hamadi, 1999) nor in a dynamic (Debruyne, 1996) setting. It was chosen in this work, because it performs reasonably well and its required extensions to dynamic and distributed settings are comparably compact.…”

Section: Future Workmentioning

confidence: 99%

An Arc-Consistency Algorithm for Dynamic and Distributed Constraint Satisfaction Problems

Ringwelski

2005

Artif Intell Rev

View full text Add to dashboard Cite

This paper presents the new DDAC4 algorithm for dynamic arc consistency enforcement in distributed constraint satisfaction problems (CSP). The algorithm is an adaptation of the well-known AC-4 algorithm to system settings where constraints can be added and deleted in concurrent processes. It is the first algorithm for arc-consistency enforcement in this system setting. Arc-consistency is achieved whenever the overall system reaches quiescence after a constraint is added or deleted.

show abstract

“…Dynamic constraint satisfaction problem (DCSP) as a set of successive static CSPs with addition or removal of constraints was first formulated in [3], and subsequently targeted in many other works [4], [5], [6], [7], [2]. A comprehensive survey of the related research is presented in [8].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Constraint Reasoning in Smart Environments

Degeler

Lazovik

2013

2013 IEEE 25th International Conference on Tools With Artificial Intelligence

View full text Add to dashboard Cite

Flexible and easily adjustable reasoning mechanisms are essential for rendering sensor and actuator rich indoor environments smart. Constraint-based solutions are a suitable approach for such systems. We propose an approach that allows users to specify the rules for a building's behavior, and uses context information to represent the rules and environment as a dynamic constraint satisfaction problem. The dependency graph data structure allows to find efficiently only the affected parts of the environment, thus minimizing the computational efforts after every event. We evaluate the system on a building implementation as a living lab, and with performance experiments. The testing proves the high efficiency and applicability of the approach for dynamic control of smart environments.

show abstract

Arc-consistency in dynamic CSPs is no more prohibitive

Cited by 16 publications

References 4 publications

Constraint Solving in Uncertain and Dynamic Environments: A Survey

Constraint Solving in Uncertain and Dynamic Environments: A Survey

An Arc-Consistency Algorithm for Dynamic and Distributed Constraint Satisfaction Problems

Dynamic Constraint Reasoning in Smart Environments

Contact Info

Product

Resources

About