Petri nets: an introduction
Prolog programming for artificial intelligence
Prolog programming for artificial intelligence
Fusion, propagation, and structuring in belief networks
Artificial Intelligence
Principles of artificial intelligence
Principles of artificial intelligence
Logical foundations of artificial intelligence
Logical foundations of artificial intelligence
A Predicate-Transition Net Model for Parallel Interpretation of Logic Programs
IEEE Transactions on Software Engineering
Visual programming by transaction network
Proceedings of the Twenty-First Annual Hawaii International Conference on Software Track
A Proof Procedure Using Connection Graphs
Journal of the ACM (JACM)
Logic for Problem Solving
Behaviour of Elementary Net Systems
Proceedings of an Advanced Course on Petri Nets: Central Models and Their Properties, Advances in Petri Nets 1986-Part I
Proceedings of an Advanced Course on Petri Nets: Central Models and Their Properties, Advances in Petri Nets 1986-Part I
Proceedings of an Advanced Course on Petri Nets: Central Models and Their Properties, Advances in Petri Nets 1986-Part I
Proceedings of an Advanced Course on Petri Nets: Central Models and Their Properties, Advances in Petri Nets 1986-Part I
A Model for Deliberation, Action, And Introspection
A Model for Deliberation, Action, And Introspection
Fuzzy Metagraph and Its Combination with the Indexing Approach in Rule-Based Systems
IEEE Transactions on Knowledge and Data Engineering
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Intelligent QoS management for multimedia services support in wireless mobile ad hoc networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Net representation, which provides a uniform semantics to a wide class of computational problems, such as numeric functions, logical systems, and models of dynamic and distributed systems, is reviewed. Using a uniform formalism of colored propositional nets, the methodology of net models is extended to represent Horn clauses, non-Horn clauses, and expert systems. It is shown that, using this formalism, tools can be built for expanding and partitioning knowledge-bases, and testing knowledge-base properties such as consistency, redundancy, and deadlocks.