Using reasoning complexity, a criterion for measuring the level of autonomy is put forward. Various architectures for different types agents, such as simple agent, deliberate agent and planning agent, are given.
提出了用推理复杂性作为度量agent自主性的标准,给出了“简单自主agent(simple agent)”、“慎思自主agent(deliberate agent)”以及“规划agent(planningagent)”等不同程度自主性的agent的结构,从而为实际应用中根据特定的应用背景选择建构具有何种推理能力的agent提供了必要的理论基础。
参考来源 - 智能体结构IASC与面向智能体程序设计语言IAPL的研究及实现·2,447,543篇论文数据,部分数据来源于NoteExpress
在智能系统的研究与开发中,推理方法的计算复杂性是一个很重要的问题。
In the research and development of intelligence system, the computing complexity of reasoning is a important problem.
由于空间问题固有的复杂性和不确定性,空间关系的描述和推理普遍采用定性方法以符合人们的空间认知行为。
Because of the complexity and uncertainty inherent in spatial space, the description and reasoning of spatial relation often use qualitative method in accordance with spatial cognition.
利用最大树法来实现对小样本案例的聚类与提取,避免了制定推理规则的复杂性。
Using maximal tree method to cluster and extract the small cases, it avoids the complexity of establishing reasoning rules.
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