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Brief summary of the group in PowerPoint. Constraint satisfaction is a decision problem that involves finite choices. It is ubiquitous. A wide range of techniques have been applied to constraint satisfaction. This includes constraint propagation, optimization, heuristics, complete search and local search methods such as neural network and evolutionary computation. For a brief explanation on what a Constraint Satisfaction Problem is, see brief tutorial (one page) or detailed tutorial (in Powerpoint). More tutorial materials can be found in CP4 To learn more about the field, consult Rossi, van Beek & Walsh (ed), Handbook of Constraint Programming, Elsevier 2006, E.P.K. Tsang, Foundations of Constraint Satisfaction, Academic Press, London, 1993, E.C. Freuder & A. Mackworth (ed.), Constraint-based Reasoning, MIT Press, 1994, R. Dechter, Constraint Processing, Morgan Kaufmann, 2003, Journal of CONSTRAINTS and research articles in recent journals and conference proceedings. To get to know more about other researchers, visit other sites in the well organized Constraint Archives or our Links to other WWW Pages. |
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| Related research: Computational Finance | ||
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Created by: Chris Voudouris; Maintained by: Edward Tsang
| BRACIL Home Page | Constraint Satisfaction & Optimization | Computational Finance & Economics |