Des études récentes font apparaître différentes limitations des systèmes experts vis-à-vis des besoins réels des utilisateurs. Nous pensons que la principale cause de ces limites tient au rôle passif et limité qui est attribué à l'utilisateur. Pour pallier ces limites, le paradigme de la coopération homme-machine (H-M) a émergé depuis quelques années dans le champ de l'ergonomie cognitive et de l'intelligence artificielle. L'objet de ce papier est d'apporter une contribution à la définition du concept de coopération H-M. Nous défendrons ainsi l'idée qu'un système coopératif est un système facilitant l'appropriation des actions et des résultats du système par l'utilisateur. Cette appropriation reposant sur la compréhensibilité et l'acceptabilité des réponses du système, la possibilité pour un système d'expliquer ses réponses devient une exigence fondamentale dans la conception de systèmes coopératifs. Le texte présente une réflexion critique sur les travaux les plus récents ayant cherché à doter les systèmes experts de capacités explicatives. L'analyse des limites de l'état de l'art sur la question nous conduit à proposer une nouvelle vision de l'explication, conçue elle-même comme un processus coopératif. En conclusion, nous discutons notre approche de la coopération H-M par rapport à celle développée dans d'autres travaux, centrés notamment sur la question de l'allocation des tâches entre l'homme et le système.

Recent studies have pointed out several limitations of expert systems regarding the actual users' needs. We believe that the main cause of these limitations corresponds to the passive and limited role assigned to the user in the processing of his/her problem. Analyzing these limitations has led to introduce the concept of human-computer cooperation at the same time in the focus of cognitive ergonomics and artificial intelligence. The purpose of this paper is to contribute to the definition of human-computer cooperation. In particular, we focus our discussion on the explanation needs required by a cooperative problem-solving process. A first section argues about the need of cooperation between the system and the user. Our argument is based on a review of studies of human cooperative dialogues. This review leads us to say that a user must be seen as a competent agent. Facing a problem, a competent agent is able to evoke a set of elements to be taken into account in the solution. The system's responses are then understood by the user with respect to this set of elements. In doing so, the user is trying to appropriate the system's actions and results. Thus, we talk about a cooperative system as a system able to enhance this user's appropriation task. Because the effectiveness of this task relies on the understandability and the acceptability of the system's responses, explanation facilities become a requirement for cooperative systems. A second section presents a review of the work on the generation of explanations. Basically, the system's explanations are based on a record of the rules fired during a problem-solving session. This record is called a reasoning trace. The reasoning trace has been augmented with support knowledge, in order to justify the rules of an expert system. We discuss the necessity of this kind of explanatory knowledge, with respect to some observations on human dialogues. In particular, we argue that trace-based explanations are not useful for users with a different competence than the system one's. In order to produce explanations satisfying different types of users, expert systems were provided with others' abilities: rhetorical schemas, user modelling technics and context-based processing of the user's requests. A last discussion argues that the construction of explanations must be conceived as a cooperative process itself. The third section concludes by discussing our approach to man-machine cooperation with respect to the one elaborated by others' studies, especially those which focus on the issue of task allocation between men and machines.