Effective reuse of KBs often entails the expensive task of identifying plausible KB-combinations. This research assists the MUSKRAT-Advisor [133] to decide whether existing KBs could be reused for solving new problems. This research assists this process, by developing an aid based on constraint satisfaction techniques which identifies incompatible KB-combinations in the scheduling domain. Incompatible KBs can be discarded, thus leaving fewer combinations for the MUSKRAT-Advisor to examine in detail. I have used a constraint solver as the Problem Solver (PS) and have represented the existing scheduling KBs as Constraint Satisfaction Problems (CSPs) which can be combined to create a composite CSP. If the composite CSP is found to be inconsist...
A constraint satisfaction problem (CSP) requires a value, selected from a given finite domain, to be...
A constraint satisfaction problem (CSP) consists of a set of variables; for each variable, a nite se...
Abstract. Complete algorithms for constraint solving typically exploit properties like (in)consisten...
Effective re-use of knowledge bases requires the identification of plausible combinations of both pr...
Constraint relaxation is a frequently used technique for managing over-determined constraint satisfa...
Since the last decade, hard combinatorial problems such as scheduling have been the target of many a...
The performance of constraint based problem solving depends crucially on the problem representation....
Conventional techniques for the constraint satisfaction problem (CSP) have had considerable success ...
This thesis explores the reuse of knowledge bases through semi-automated code generation of new KBs ...
A constraint satisfaction problem (CSP) requires a value, selected from a given finite domain, to be...
AbstractConstraint propagation is an elementary method for reducing the search space of combinatoria...
We introduce a new method, called constraint-directed-generate-and-test (CDGT), for solving constrai...
Constraint Satisfaction Problems (CSPs) involve assigning values to a finite set of variables from...
Constraint Satisfaction is a flexible paradigm for modeling many decision problems in Engineering, C...
The influence of graph-related properties on constraint satisfaction problems (CSP) has been investi...
A constraint satisfaction problem (CSP) requires a value, selected from a given finite domain, to be...
A constraint satisfaction problem (CSP) consists of a set of variables; for each variable, a nite se...
Abstract. Complete algorithms for constraint solving typically exploit properties like (in)consisten...
Effective re-use of knowledge bases requires the identification of plausible combinations of both pr...
Constraint relaxation is a frequently used technique for managing over-determined constraint satisfa...
Since the last decade, hard combinatorial problems such as scheduling have been the target of many a...
The performance of constraint based problem solving depends crucially on the problem representation....
Conventional techniques for the constraint satisfaction problem (CSP) have had considerable success ...
This thesis explores the reuse of knowledge bases through semi-automated code generation of new KBs ...
A constraint satisfaction problem (CSP) requires a value, selected from a given finite domain, to be...
AbstractConstraint propagation is an elementary method for reducing the search space of combinatoria...
We introduce a new method, called constraint-directed-generate-and-test (CDGT), for solving constrai...
Constraint Satisfaction Problems (CSPs) involve assigning values to a finite set of variables from...
Constraint Satisfaction is a flexible paradigm for modeling many decision problems in Engineering, C...
The influence of graph-related properties on constraint satisfaction problems (CSP) has been investi...
A constraint satisfaction problem (CSP) requires a value, selected from a given finite domain, to be...
A constraint satisfaction problem (CSP) consists of a set of variables; for each variable, a nite se...
Abstract. Complete algorithms for constraint solving typically exploit properties like (in)consisten...