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A hierarchical model of agent based on skill, rules, and knowledge

机译:基于技能,规则和知识的代理的分层模型

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The principal aim of this research is to structure agents according to different situations that have to deal with. To achieve this, we propose a conceptual model with a hierarchical structure defined by the skill-rule-knowledge (S-R-K) levels. At the skill level, the agent deals with routines and her behavior is governed by stored patterns of predefined procedures, that map directly an observation (i.e. perception) to an action. The rule-based level represents more conscious behavior and it deals with familiar situations. This behavior is generally conventionally described by a set of heuristics. Finally, the knowledge-based level accounts for unfamiliar situations for which know-how or rules are not available. An implementation of this model has been done in the context of a multiagent environment to confirm our mean expectation: the perceptual processing (i.e., S and R levels) is fast, effortless and is propitious for coordinatedactiween agents, whereas the analytical problem solving (i.e., K level) is slow, laborious and can lead to conflicts between agents.
机译:这项研究的主要目的是根据必须处理的不同情况构造代理。为此,我们提出了一种概念模型,该模型具有由技能规则知识(S-R-K)级别定义的分层结构。在技​​能级别,代理处理例程,并且她的行为由预定义过程的存储模式控制,这些预定义过程将观察(即感知)直接映射到动作。基于规则的级别代表更自觉的行为,并且处理熟悉的情况。通常,通常通过一组启发式方法来描述此行为。最后,基于知识的级别解决了不熟悉的情况,这些情况下没有专有技术或规则。该模型的实现已在多主体环境中完成,以确认我们的平均期望:感知处理(即S和R级别)快速,轻松,并且有利于主体之间的协作,而分析性问题的解决(即,K级)缓慢,费力,并且可能导致代理之间发生冲突。

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