Agent-Based Defeasible Control in Dynamic Environments - download pdf or read online

By John-Jules Ch. Meyer, Jan Treur

ISBN-10: 9048161096

ISBN-13: 9789048161096

ISBN-10: 9401717419

ISBN-13: 9789401717410

This quantity, the seventh quantity within the DRUMS instruction manual sequence, is a part of the aftermath of the profitable ESPRIT undertaking DRUMS (Defeasible Reasoning and Uncertainty administration structures) which happened in levels from 1989- 1996. within the moment degree (1993-1996) a piece package deal was once brought dedicated to the subjects Reasoning and Dynamics, overlaying either the subjects of "Dynamics of Reasoning", the place reasoning is considered as a strategy, and "Reasoning approximately Dynamics", which needs to be understood as referring to how either designers of and brokers inside dynamic structures may well cause approximately those structures. the current quantity offers paintings performed during this context prolonged with a few paintings performed by means of impressive researchers outdoor the undertaking on similar concerns. whereas the former quantity during this sequence had its concentrate on the dynamics of reasoning professional­ cesses, the current quantity is extra all for "reasoning approximately dynamics', viz. how (human and synthetic) brokers cause approximately (systems in) dynamic environments as a way to keep an eye on them. specifically we ponder modelling frameworks and conventional agent types for modelling those dynamic structures and formal methods to those platforms similar to logics for brokers and formal capability to cause approximately agent­ established and compositional structures, and motion & swap extra ordinarily. We take this chance to say that we have got very friendly reminiscences of the venture, with its full of life workshops and different conferences, with the numerous websites and researchers concerned, either inside of and out of doors our personal paintings package.

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An option for more fine-grained control is to COMPOSITIONAL DESIGN OF MULTI-AGENT SYSTEMS 43 dynamically generate goals (targets) for the reasoning process within a (primitive) component, thus supporting dynamic control of limited reasoning within a component. Another option for more fine-grained control is to dynamically generate additional presuppositions (assumptions) for the reasoning process in a component. In this section the control of reasoning by dynamic targets and by dynamic assumptions is discussed.

This language construct is used to define object-meta relations in the reasoning process. T. M. JONKER AND J. 3 Knowledge bases A knowledge base defines a part of the knowledge that is used in one or more of the processes. Knowledge bases use ontologies defined in information types. Which information types are used in a knowledge base defines a relation between information types and knowledge bases. In a detailed design, knowledge bases are specified in order-sorted predicate logic form, normalised to a classical rule 33 COMPOSmONAL DESIGN OF MULTI-AGENT SYSTEMS format (implications between conjunctions of literals).

T. M. JONKER AND J. TREUR transferred to the output interface of Hypothesis Validation (20), and from there to the output interface of Diagnostic Reasoning (21 ). The new observation to be performed, is transferred to the component External World (22), where it is actually performed (23). The observation result (not noise) is transferred to the component Diagnostic Reasoning (24 ), and further down to Hypothesis Validation (25) and Hypothesis Evaluation (26). This time this component is able to derive that one of the specific hypotheses (broken engine) is true (27).

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Agent-Based Defeasible Control in Dynamic Environments by John-Jules Ch. Meyer, Jan Treur

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