Research On Configuration Explained Algorithm Of Constraint Satisfaction Problem

In recent years, the configuration problems is a hot issue in study ,is an important branch of the research in the field of artificial intelligence. By the concern of many researchers .With the development of society, more and more problems were representation as configuration problems .People on the solve of configuration for the demand put forward higher, require- ments .Configuration tasks are completed mainly divided into two areas, On the one hand is the issue of how to describe configuration tasks ,We call it the know- ledge representation, On the other hand what is described in this field of knowledge to solve problems .We call configuration solution. At present ,there are many method of knowledge representation for the respect of knowledge representation .More popular method of represent the area of configuration knowledge with logic and CSP(Constraint Satisfaction Problems).Constraint Satisfaction Problems is an important and fundament problem .It is a method to represent the configuration task. Manifested as a kind of mapping, Corresponding the relevant elements of Constraint Satisfaction Problems with the relevant elements of configuration. Configuration was represent as Dynamic Constraint Satisfaction problems with the interactive relationship between users and configuration .It clearly the elements of part of decision-making in configuration task Thus we transformation the configuration task into a Constraint Satisfaction Problem .How to proceed from a collection of variables ,and seek to meet various constraints relations between the variable values is the fundamental problem of Constraint Satisfaction Problems .There are many research results for Constraint Satisfaction problem .and some good research results can be applied on the Constraint Satisfaction Problem in the area of configuration.This paper mainly on the research the method for the explain of the configuration problems .this is on the basis of the representation of configuration with Constraint Satisfaction Problem .with the idea to find a better method to answer to the problem in configuration task and good guide users to configure .In order to a better research .first this paper describes the concepts of configuration and Constraint Satisfaction Problem .Also we describes the relationship between the mapping of them .On the basis of this paper mainly research and analysis the algorithms for explain on the frameworks of this .At present ,algorithm of explain mainly divided into two types. Intrusive(have the ability to judge and record explanations in constraint propagation)and non-intrusive(solving explanation independent of the constraint propagation process).The intrusive method increased the system complexity of solution space for record explanations in constraint propagation process .It will increase the storage configuration information for the burden .In support of multi-user configuration solver , It would need to store a large amount of information relating to explanation if too many users use solver .It is a thorny issue about how to sore the information .This paper describes TMS methods such as representatives of the algorithm .To address this issue the non-intrusive methods without recorded information in the constraint propagation is very important .This paper describes two typical of such approaches AOP and QuickXplain.The AOP use AOP method the expansion of OOP implementation separation between interpretation of the solution and constraint solving .This method has many limitations not apply in many configuration solving ,This paper with basis of QuickXplain In the interactive configuration the current decision-making impact the explain of configuration .Give a method of solving explanation based on the current constraint satisfaction problem .Over-constrained problems(the problem has not been a viable solution)expected the conflict is exponential. And also the corresponding explanation is exponential .How to look for a better explanation in such a large of explanations is a issue need to solve. A solution is: first allow users to determine the priority of parameters. In interactive configuration it is that users preferences there favorite parts .So we defines the parameters of the order with the priority order.So if the current decision-making is conflict ,then the decision made recently by the user is a part of the conflict .At this point the problem is a over-constraint problem .For this problem the recently decision-making as a constraint in the constraints in the knowledge .We abstract the current issue into a conflict for the optimal based on the principle of QuickXplain.We get the optimal solution through the issue divided into two sub-problems with the same way .In the view of the current decision-making involved in the conflict may not be a constraint issues .This paper come through: the optimal number of constraints conflict sets each constraint is the solving set of the conflict and set. And with the other methods of solving algorithm that in configuration the solution has its advantages, in some areas. This paper give a simple example of the testing of experimental data shows that the algorithm running time (consistency of performance for the number of detections) and the number of conflicts and the number of parameters is closely linked to verify when given a control, Time is running the algorithm can be expected (in a certain range).In this case the algorithm is an effective method to solve.This paper analyzes the explained method in the original configuration. The explained method in the original configuration is through consistency constraints set for conflict .This task provided with the original allocation algorithm integration possible .This paper give the map for the relationship between the various objects of our algorithm is involved with the function of the main targets of the relationship. Another explanation is part of the solution solve explanation is a tools explained the failure and guide users, It service the configuration. This paper analysis the solving thinking on the original configuration and the relationship between configuration solve and explanation .This paper also give a map of configuration solve .That is using java object-oriented method.In short, based on the current decision-making constraint satisfaction problems configuration can direct and effective give users the explanation for the failure of the optimal. The algorithm can show good prospects in dealing with multiple constraints and consider users preferences.