Editing Constraint satisfaction problem (section)

===Dynamic CSPs===
'''Dynamic CSPs'''<ref>Dechter, R. and Dechter, A., [http://www.ics.uci.edu/%7Ecsp/r5.pdf Belief Maintenance in Dynamic Constraint Networks] {{Webarchive|url=https://web.archive.org/web/20121117042241/http://www.ics.uci.edu/%7Ecsp/r5.pdf |date=2012-11-17 }} In Proc. of AAAI-88, 37–42.</ref> (''DCSP''s) are useful when the original formulation of a problem is altered in some way, typically because the set of constraints to consider evolves because of the environment.<ref>[http://www.aaai.org/Papers/AAAI/1994/AAAI94-302.pdf Solution reuse in dynamic constraint satisfaction problems], Thomas Schiex</ref> DCSPs are viewed as a sequence of static CSPs, each one a transformation of the previous one in which variables and constraints can be added (restriction) or removed (relaxation). Information found in the initial formulations of the problem can be used to refine the next ones. The solving method can be classified according to the way in which information is transferred:
* [[Oracle machine|Oracles]]: the solution found to previous CSPs in the sequence are used as heuristics to guide the resolution of the current CSP from scratch.
* Local repair: each CSP is calculated starting from the partial solution of the previous one and repairing the inconsistent constraints with [[Local search (optimization)|local search]].
* Constraint recording: new constraints are defined in each stage of the search to represent the learning of inconsistent group of decisions. Those constraints are carried over to the new CSP problems.