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 venture DRUMS (Defeasible Reasoning and Uncertainty administration platforms) which came about in levels from 1989- 1996. within the moment degree (1993-1996) a piece package deal was once brought dedicated to the themes Reasoning and Dynamics, protecting either the themes of "Dynamics of Reasoning", the place reasoning is considered as a approach, and "Reasoning approximately Dynamics", which has to be understood as relating how either designers of and brokers inside of dynamic structures may possibly cause approximately those platforms. the current quantity provides paintings performed during this context prolonged with a few paintings performed via extraordinary researchers outdoors the venture on comparable concerns. whereas the former quantity during this sequence had its specialize in the dynamics of reasoning seasoned cesses, the current quantity is extra serious about "reasoning approximately dynamics', viz. how (human and synthetic) brokers cause approximately (systems in) dynamic environments with a purpose to keep an eye on them. particularly we contemplate modelling frameworks and primary agent types for modelling those dynamic platforms and formal techniques to those platforms corresponding to logics for brokers and formal capability to cause approximately agent established and compositional structures, and motion & switch extra ordinarily. We take this chance to say that we've got very friendly reminiscences of the undertaking, with its full of life workshops and different conferences, with the numerous websites and researchers concerned, either inside of and outdoors our personal paintings package.
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Additional info for Agent-Based Defeasible Control in Dynamic Environments
The result is an evaluation of the hypotheses (Epistemic Domain Hypotheses) on which evaluation focussed. T. M. JONKER AND J. 3 Specification of abstraction levels The identified levels of process abstraction are modelled as abstraction/specialisation relations between components at adjacent levels of abstraction: components may be composed of other components or they may be primitive. Primitive components may be either reasoning components (based on a knowledge base), or, alternatively, components capable of performing tasks such as calculation, information retrieval, optimisation, et cetera.
However, at that time broken bulb was not a target of this component, and therefore it was not derived. Only after the targets of Hypothesis evaluation had been changed and included broken bulb (18), was it actually derived (19). This shows how targets dynamically influence the reasoning behaviour of the system. COMPOSITIONAL DESIGN OF MULTI-AGENT SYSTEMS 47 Figure 17. Second example trace description time points Diagnostic Reasoning 5 6 7 8 9 10 11 12 13 14 15 16 [not light, cold j; [confirmed(fridge_problem)] [confirmed(fridge_problem), selected _observation(light).
If either the engine or the cooling system is broken, the fridge is said to have a cooling problem. In Figure 11 this taxonomy of types of problems is depicted. fridge problem cooling problem electricity problem broken bulb no power supply broken engine Figure 11. T. M. JONKER AND J. , observations imply faults) manner. For reasons of presentation, the anti-causal manner is chosen. system The component Hypothesis Determination uses the following knowledge bases: Hypothesis Refinement KB (domain independent knowledge) if confirmed(H:HYPOTHESIS) and subhypothesis_of(Hl:HYPOTHESIS, H:HVPOTHESIS) and not tried(Hl:HYPOTHESIS) then focus_hypothesis(Hl:HYPOTHESIS) Subhypotheses KB (domain specific knowledge) , electricity _problem) subhypothesis_of(broken_bulb , electricity _problem) _supply no_power subhypothesis_of( , cooling_problem) subhypothesis_of(broken_engine subhypothesis_of(broken_cooling_system , cooling_problem) , fridge_problem) subhypothesis_of( cooli ng_problem , fridge_problem) subhypothesis_of(electricity _problem The domain specific knowledge base Subhypotheses KB represents the knowledge depicted in a graphical form in Figure 11 (the taxonomy).
Agent-Based Defeasible Control in Dynamic Environments by John-Jules Ch. Meyer, Jan Treur