A shared workspace to support man–machine reasoning: application to cooperative distant diagnosis

This paper focuses on man–machine cooperation problems. In particular, it deals with those problems that occur when both human and machine have to achieve a shared reasoning activity. It puts forward a man–machine approach that is dedicated to technical diagnosis problem solving. Coordination of human and automated reasoning is key to solving this problem, since efficiency depends on both sharing and interpreting exchanged data. A shared workspace is proposed to support both machines and their human operators. This workspace is kept as close as possible to human representations in order to reduce cooperation costs. The paper describes those coordination mechanisms that are able to support such a cooperative activity using a shared workspace. In order to assess the costs and benefits of such cooperation, these mechanisms are applied to a complex industrial problem: diagnosis and troubleshooting in a phone network. The results show the full impact of cooperation on human–machine reasoning.

[1]  David Jouglet Coopération homme-machine pour le diagnostic technique : Application aux dérangements téléphoniques , 2000 .

[2]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[3]  Allen Newell,et al.  The psychology of human-computer interaction , 1983 .

[4]  Peter F. Patel-Schneider,et al.  Device Representation and Reasoning with Affective Relations , 1995, IJCAI.

[5]  L. Bainbridge Ironies of Automation , 1982 .

[6]  Sylvain Piechowiak,et al.  Cooperative Diagnosis Support Tool Including a Multi-Point of View Modelling , 1998 .

[7]  Giovanni Guida,et al.  Functional and teleological knowledge in the multimodeling approach for reasoning about physical systems: a case study in diagnosis , 1993, IEEE Trans. Syst. Man Cybern..

[8]  Frédéric Vanderhaegen,et al.  Cooperative system organisation and task allocation : Illustration of task allocation in air traffic control , 1999 .

[9]  Randall Davis,et al.  Diagnostic Reasoning Based on Structure and Behavior , 1984, Artif. Intell..

[10]  Jens Rasmussen,et al.  Information Processing and Human-Machine Interaction , 1986 .

[11]  Michaël Rusinowitch,et al.  Preferring diagnoses by abduction , 1993, IEEE Trans. Syst. Man Cybern..

[12]  Raymond Reiter,et al.  A Theory of Diagnosis from First Principles , 1986, Artif. Intell..

[13]  Jens Rasmussen,et al.  Information Processing and Human-Machine Interaction: An Approach to Cognitive Engineering , 1986 .

[14]  David Poole,et al.  Explanation and prediction: an architecture for default and abductive reasoning , 1989, Comput. Intell..

[15]  Béchir El Ayeb Méthodes, langages et outils de spécification et de construction des systèmes de diagnostic , 1989 .

[16]  W Van de Velde Naive causal reasoning for diagnosis , 1986 .