The Unified Problem-Solving Method Development Language UPML

Fensel, Dieter; Motta, Enrico; Harmelen, Frank van; Benjamins, V. Richard; Crubézy, Monica; Decker, Stefan; Gáspari, Mauro; Available, Not Available Not; Groenboom, Rix; Grosso, William; Musen, Mark A.; Plaza, Enric; Schreiber, Guus; Studer, Rudi; Wielinga, B.J.

doi:10.1007/s10115-002-0074-5

Cited by 67 publications

(38 citation statements)

References 8 publications

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“…The Unified Problem-solving Method Language (UPML) [18] is a de facto standard that describes the components of a PSM as: (1) tasks, they describe the operation to be solved in the execution of a method that solves such task, specifying the input/output parameters and the pre/post-conditions (competence) required to be applicable (this description is independent of the method used for solving the task); (2) methods, elements that detail the control of the reasoning process to achieve a task; and (3) adapters [19] specify mappings among the knowledge components of a PSM. The adapters are used to achieve the reusability at the knowledge level, since they bridge the gap between the general description of a PSM and the particular domain where it is applied.…”

Section: Problem-solving Methods Ontologymentioning

confidence: 99%

Development of Semantic Web Services at the Knowledge Level

2004

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Abstract. Web Services are interfaces to a collection of operations that are network-accessible through standardized XML messaging, and whose features are described using standard XML-based languages. Semantic Web Services (SWS) describe semantically the internal structure and the functional/nonfunctional capabilities of the services, facilitating the design and evaluation of SWSs based on that semantic description of the features of the services. To enable users to design and compose SWSs at the knowledge level, the ODE SWS framework has been proposed. That framework uses problem-solving methods to describe the functional and structural features of the SWSs. In this work, we present a description of the ODE SWS environment as an implementation of the ODE SWS framework. Specially, we focus on the description of the capabilities of the SWSDesigner, the tool of the ODE SWS environment that enables users to design graphically SWSs through different but complementary views of the services.

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Section: Problem-solving Methods Ontologymentioning

confidence: 99%

Development of Semantic Web Services at the Knowledge Level

2004

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“…Another approach, OntoKADS, extends CommonKADS by way of introducing ontologies to comprise the expertise model (Bruaux et al, 2005). UPML (Fensel, Motta et al, 2002) encapsulated previous approaches to describing general task and problem-solving knowledge with general ontologybased PSM structures. One limitation in UPML is the absence in consideration given to PSMs for tasks where multiple software components are required to interact in order to solve a problem.…”

Section: Background and Related Workmentioning

confidence: 99%

“…Following the reuse paradigm promoted in single agent knowledge-based systems development (Schreiber et al, 2001), the work in (Beydoun et al, 2006) proposes a process that revolves around a domain-dependant ontology to build individual agents with problem-solving methods (PSMs). PSMs are high-level structures describing a reasoning process employed to solve general types of problems (Fensel et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

Towards Problem Solving Methods in Multi-Agent Systems

2009

Proceedings of the 4th International Conference on Software and Data Technologies

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Problem Solving Methods (PSM) are abstract structures that describe specific reasoning processes employed to solve a set of similar problems and have proved very effective at enhancing reuse and extensibility in developing knowledge-based systems. We envisage that off-the-shelf PSMs can similarly assist in the development of agent-oriented solutions using Multi-Agent Systems (MAS). A challenge towards the effective use of PSMs in MAS is that current approaches to formulating PSMs do not adequately address the complexity of problems to which agent-oriented systems are suited. Towards addressing this, this paper focuses on providing an approach to guide developers in adequately formulating PSMs for complex problemsolving where interactions are involved, such as in domains where negotiation and cooperation are essential for solving a problem. Knowledge engineering, multi-agent system methodologies, problem-solving methods. TOWARDS PROBLEM SOLVING METHODS IN MULTI-AGENT SYSTEMS Abstract:Problem Solving Methods (PSM) are abstract structures that describe specific reasoning processes employed to solve a set of similar problems and have proved very effective at enhancing reuse and extensibility in developing knowledge-based systems. We envisage that off-the-shelf PSMs can similarly assist in the development of agent-oriented solutions using Multi-Agent Systems (MAS). A challenge towards the effective use of PSMs in MAS is that current approaches to formulating PSMs do not adequately address the complexity of problems to which agent-oriented systems are suited. Towards addressing this, this paper focuses on providing an approach to guide developers in adequately formulating PSMs for complex problem-solving where interactions are involved, such as in domains where negotiation and cooperation are essential for solving a problem.

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“…This level, often called ontology, materializes the domain knowledge; -the inference layer can be seen as a library of problem solving methods and processes described in a declarative manner; -the task layer provides a procedural interpretation of the inference layer. More recently, a similar perspective was used to structure the Unified Problem-solving Methods Language (UPML) [32]. In UPML, three major component types are defined: task, domain model and problem solving method (PSM).…”

Section: Proposed Approach For Experience Feedbackmentioning

confidence: 99%

Knowledge formalization in experience feedback processes: An ontology-based approach

Foguem

Coudert

Béler

et al. 2008

Computers in Industry

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Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, Knowledge Management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an Experience Feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving the missions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable.

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The Unified Problem-Solving Method Development Language UPML

Cited by 67 publications

References 8 publications

Development of Semantic Web Services at the Knowledge Level

Development of Semantic Web Services at the Knowledge Level

Towards Problem Solving Methods in Multi-Agent Systems

Knowledge formalization in experience feedback processes: An ontology-based approach

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