Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Autonomous Control Approach for Local Search
SLS '09 Proceedings of the Second International Workshop on Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics
A Hyperheuristic Approach to Select Enumeration Strategies in Constraint Programming
ACT '09 Proceedings of the 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies
Adaptive enumeration strategies and metabacktracks for constraint solving
ADVIS'06 Proceedings of the 4th international conference on Advances in Information Systems
Using autonomous search for generating good enumeration strategy blends in constraint programming
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
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Autonomous Search (AS) is a special feature allowing systems to improve their performance by self-adaptation. This approach has been recently adapted to Constraint Programming (CP) reporting promising results. However, as the research lies in a preliminary stage there is a lack of implementation frameworks and architectures. This hinders the research progress, which in particular, requires a considerable work in terms of experimentation. In this paper, we propose a new framework for implementing AS in CP. It allows a dynamic selfadaptation of the classic CP solving process and an easy update of its components, allowing developers to define their own AS-CP approaches. We believe this will help researchers to perform new AS experiments, and as a consequence to improve the current preliminary results.