Problem-Solving Method (PSM)

Context:
- It can operate at the Knowledge Level.
- It can provide Abstract Procedures.
- It can allow for Operations on Propositional Knowledge.
- ...
Example(s):
Counter-Example(s):
- Genetic Algorithm,
- Inference Algorithm.
See: Heuristic Classification, SALT System, Protégé-II, Unified Problem-Solving Method Description Language (UPML).

References

Web Chatbot
- The Problem-Solving Method is a complex process employed to identify and solve issues or obstacles faced by individuals or groups. The process can be split into various stages that are not necessarily sequential. The stages include identifying the problem, defining it, forming a problem-solving strategy, organizing the necessary information, assigning needed resources to it, and monitoring the progression of the solution. Finally, the results are evaluated to affirm if the best possible solution has been found. The method requires the accurate identification and definition of the problem, generation of multiple potential solutions without immediate judgement, organization of available information to pinpoint the most accurate solution, and a strategic allocation of resources. The process also calls for consistent monitoring of the problem-solving progression. If the process is not heading towards the desired results, then the approach should be reassessed and new strategies should be considered. The application of this method is present in multiple contexts, including team problem-solving within companies. However, such application is often hindered by challenges like inefficiency or overly cautious approaches. To increase efficiency, a collaborative approach is recommended, especially when dealing with complex problems.

(Fensel et al., 2003) ⇒ Dieter Fensel, Enrico Motta, Frank van Harmelen, V. Richard Benjamins, Monica Crubezy, Stefan Decker, Mauro Gaspari, Rix Groenboom, William Grosso, Mark Musen, Enric Plaza, Guus Schreiber, Rudi Studer and Bob Wielinga. (2003). “The Unified Problem-Solving Method Development Language UPML.” In: Journal Knowledge and Information Systems, 5(1). doi:10.1007/s10115-002-0074-5.
- Problem-solving methods provide reusable architectures and components for implementing the reasoning part of knowledge-based systems. The Unified Problem-Solving Method Description Language (UPML) has been developed to describe and implement such architectures and components to facilitate their semi-automatic reuse and adaptation. In a nutshell, UPML is a framework for developing knowledge-intensive reasoning systems based on libraries ofg eneric problem-solving components. The paper describes the components and adapters, architectural constraints, development guidelines, and tools provided by UPML. UPML is developed as part of the IBROW project, which provides an Internet-based brokering service for reusing problem-solving methods.

(Gennari et al., 2003) ⇒ John H. Gennari, Mark A. Musenb, Ray W. Fergersonb, William E. Grossod, Monica Crubézyb, Henrik Erikssonc, Natalya F. Noyb, and Samson W. Tub. (2003). “The Evolution of Protégé: an environment for knowledge-based systems development Daniel S. Weld.” In: International Journal of Human-Computer Studies. [http://dx.doi.org/10.1016/S1071-5819(02)00127-1 doi:10.1016/S1071-5819(02)00127-1
- The most significant difference between the original Protégé and the Protégé-II version was the idea of reusable problem-solving methods. Following Chandrasekaran (1983; 1986), Protégé-II allowed developers to build inference mechanisms in an entirely separate component, a problem-solving method, which could be developed independently from the knowledge base. These problem-solving methods (PSMs) were generic algorithms that could be used with different knowledge bases to solve different real-world tasks. Examples of PSMs include the episodic planning algorithm used by Protégé-I, and methods such as “propose-and-revise” used by the SALT system to solve constraint satisfaction problems. As Figure 5a shows, Protégé was initially designed with a single problem-solving method (the ESPR method) which could be applied to different knowledge bases. Figure 5b shows the shift to a more generic, component-based approach, where alternative PSMs are applied to knowledge bases.

(Fensel, 2000) ⇒ D. Fensel. (2000). “Understanding, Development, Description, and Reuse of Problem-Solving Methods.” In: Lecture Notes in Artificial Intelligence (LNAI), Springer-Verlag.

(Benjamins & Fensel, 1998) ⇒ V. R. Benjamins and D. Fensel. (1998). “Special Issue on Problem-Solving Methods.” International Journal of Human-Computer Studies (IJHCS), 49(4): 305-313.
(Benjamins & Shadbolt, 1998) ⇒ V. R. Benjamins and Nigel Shadbolt. (1998). “Special Issue on Knowledge Acquisition and Planning.” International Journal of Human-Computer Studies (IJHCS), 48(4).

(Stefik, 1995) ⇒ M. Stefik. (1995). “Introduction to Knowledge Systems.” Morgan Kaufman.

(Chandrasekaran, 1986) ⇒ Balakrishnan Chandrasekaran. (1986). “Generic Tasks in Knowledge-based Reasoning: High-level Building Blocks for Expert-System Design.” In: IEEE Expert, 1.

(Clancey, 1985) ⇒ W. J. Clancey. (1985). “Heuristic Classification.” In: Artificial Intelligence, 27(1-2).