Causal Reasoning: A Systems Approach
Casual reasoning is an active area of research in the field of artificial intelligence, and significant new techniques have recently emerged. To date, however, there has been little synthesis with traditional expert system approaches based on heuristic knowledge. In this book it is shown how such a synthesis can be achieved within a system-theoretic framework. The systems approach provides a powerful methodology for analyzing casual mechanisms in physical systems. It provides a sound foundation for developing reliable real-time software casts new light on qualitative reasoning and knowledge-based approaches.
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applicable relation Artificial Intelligence atomic atomic-system axis-sets basis behaviour causal clause common domain compiled knowledge complex-system composition equations conjunctive abstraction conjunctive-abstraction constraints control action control algorithm control voltage control-input corresponding countable sets Coupled-Tanks cybernetics definitions denotes deterministic system disjunctive-abstraction domain-specific predicates error-negative error-positive event-history event-times Expert System Fuzzy Logic Control Fuzzy Sets given goal input and output input function knowledge representation knowledge-base kth level level of abstraction levell-increasing levell-steady linguistic logical conjunction Logical Space many-valued logic many-valued predicates maximum number measurement data non-deterministic number of events number of rules number of state-variables obtained orthogonal output-function overall response function parameters phase physical controls physical system PID controller possible predicate names pressure error Prolog QST provides Qualitative Physics range rules required sensor set-point shell specific predicate specified state-space state-transition function subset System Theory system-topology tank temporal operators Theorem time-invariant systems time-stamp tion topology transition function truth value Tval
Page 111 - Mamdani, EH, Procyk, TJ, and Baaklini, N. (1976) "Application of fuzzy logic controller design based on linguistic protocol", Proc. Workshop on discrete systems and fuzzy reasoning, Queen Mary College, London.