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

By John-Jules Ch. Meyer, Jan Treur

This quantity, the seventh quantity within the DRUMS guide sequence, is a part of the aftermath of the profitable ESPRIT undertaking DRUMS (Defeasible Reasoning and Uncertainty administration platforms) which happened in levels from 1989- 1996. within the moment level (1993-1996) a piece package deal was once brought dedicated to the themes Reasoning and Dynamics, masking either the subjects of "Dynamics of Reasoning", the place reasoning is considered as a procedure, and "Reasoning approximately Dynamics", which needs to be understood as bearing on how either designers of and brokers inside of dynamic platforms could cause approximately those platforms. the current quantity offers paintings performed during this context prolonged with a few paintings performed by way of impressive researchers outdoor the venture on comparable concerns. whereas the former quantity during this sequence had its concentrate on the dynamics of reasoning seasoned­ cesses, the current quantity is extra interested by "reasoning approximately dynamics', viz. how (human and synthetic) brokers cause approximately (systems in) dynamic environments to be able to keep an eye on them. specifically we reflect on modelling frameworks and frequent agent types for modelling those dynamic structures and formal techniques to those platforms reminiscent of logics for brokers and formal skill to cause approximately agent­ dependent and compositional structures, and motion & swap extra normally. We take this chance to say that we've got very friendly reminiscences of the venture, with its energetic workshops and different conferences, with the numerous websites and researchers concerned, either inside and outdoors our personal paintings package.

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TREUR 50 • evaluating the derived facts (meta-level reasoning) • deciding to reject some of the assumptions and/or to choose a new set of assumptions based on this evaluation (meta-level reasoning). and so on As an example, if an assumption 'a is true' has been chosen, and the facts derived from this assumption contradict information that is obtained from a different source, the assumption 'a is true' may be rejected and the converse 'a is false' may be assumed. This reasoning pattern also occurs in diagnostic reasoning based on causal knowledge (discussed below).

Overview ofthe components The generic model is not specified in detail. Instead, the components and information links are depicted in Figure 19, and relevant parts of the detailed design are presented. External World This component is used for executing observations. It has no knowledge base. starts, lights_work true(A:OA), false(A:OA), known(A:OA) Observation Result Prediction Based on the assumption, observations are predicted. T. M. JONKER AND J. TREUR Assumption Determination Based on the current state of one diagnostic process, assumptions are generated.

Analysing all specific hypotheses, for example, for a binary tree of depth n entails validation of 2n specific hypotheses, whereas for hierarchical classification following the taxonomy from top to bottom, two hypotheses per level need to be analysed, entailing validation of only 2n hypotheses for the whole process. 5 THE DESIRE SOFIWARE ENVIRONMENT The DESIRE design method is supported by the DESIRE software environment. This environment includes tools to support all phases of design. Graphical editors, for example, support specification of conceptual and detailed design of processes and knowledge.

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