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Muskrat-II from University of Aberdeen

The MUSKRAT (Multistrategy Knowledge Refinement and Acquisition Toolbox) framework aims to unify problem solving, knowledge acquisition and machine learning in a single computational framework (WHITE, SLEEMAN, 1998). Given a set of Knowledge Bases (KBs) and Problem Solvers (PSs), the system will try to identify which KBs could be combined with which PSs to solve a given task.

Muskrat-II fact-file

Owner  :  University of Aberdeen
Demonstration  :  http://www.csd.abdn.ac.uk/~tnordlan/PhD_Timetable/Programs/CSPs Suite/CSP-Suite.zip
Screencam  :  http://www.csd.abdn.ac.uk/~tnordlan/PhD_Timetable/Programs/CSPs Suite/CSP-Suite_Ver1.90.avi
Builds on  :  Java, SICStus Prolog
Addresses challenges  :  Knowledge Reuse

Towards a Solution

In this research, KBs with certain PSs will be represented as Constraint Satisfaction Problems (CSPs). By systematically relaxing each CSP by removing specific constraints we will produce a series of Cheaper Meta PSs (see Figure 1). The idea is that instead of solving all the CSPs we only need to solve those that have a solution when relaxed. This approach would be beneficial if it saves time in identifying re-usable PS. To determine the best means to relax the CSPs we have proposed building a Case-library, which will suggest dropping specific constraints that correspond to the highest search effort (Nordlander, 2002).


 Figure 1: The process of creating the Cheaper Meta Problem Solvers

Take a Guided Tour

This Movie clip(AVI, 27.3 MB), (Flash, MB), (MOV, 88.7MB) shows a how the Cheaper Meta PSs are produced, solved and compared against the original CSP.

Try a Demonstration

Version 1.90 (ZIP, 19 KB), including full online documentation, downloadable. For installation instructions email Tomas Eric Nordlander.
Technical requirements: SICStus Prolog LINUX, UNIX or any Windows version.

Further Reading

Publication regarding MUSKRAT, A Constraint-Based Approach to the Description & Detection of Fitness-for-Purpose., and Exploration on Relaxation Strategies in Random Binary Constraint Satisfaction Problems together with other relevant documents can be accessed:

http://www.csd.abdn.ac.uk/~tnordlan/Publications.htm (Tomas Eric Nordlander)

http://www.csd.abdn.ac.uk/~sleeman/dhs-publications.html (Derek Sleeman)

Semantic representation

View in the AKT Triplestore Browser or as RDF.

Also available in DOAP RDF (Description Of A Project)