Abstract
An intelligent decision system (IDS) uses artificial intelligence principles to deliver automated, interactive decision analysis (DA) consultations. Network methods adapted from operations research underlie two key IDS components: influence diagrams and activity graphs. Influence diagrams, which are familiar to DA researchers and practitioners, represent decision problems inevent space. Activity graphs, which are introduced in this paper, represent processes inaction space. While activity graphs can represent any process, we use them as a knowledge-engineering and programming language to represent the process knowledge of skilled decision analysts in the context of a specific class of decisions. This paper defines activity graphs as an extension of directed AND-OR graphs. Anactivity tree is a directed AND-OR tree consisting of nodes, which may contain activities (small computer programs) and connectors that establish logical relationships among nodes and define logical resolution agendas. Anactivity graph is a directed, multiply connected network of activity trees. Activity graphs may involve recursion. Development of the activity graph language is motivated by our desire to enable professional decision analysts — or other experts — with limited advanced programming experience to design and build consultation systems that combine the guidance offered by protocol systems with the flexibility and generality of transaction systems. This paper defines the activity graph language in detail. A simple example illustrates key concepts. The paper also discusses our experience using a computer system that implements activity graphs for developing commercial IDSs.
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Holtzman, S., Regan, P.J. Activity graphs: A language for flexible consultation systems. Ann Oper Res 65, 127–155 (1996). https://doi.org/10.1007/BF02187329
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DOI: https://doi.org/10.1007/BF02187329