Constructing Abstraction Hierarchies Using a Skill-Symbol Loop.

George Konidaris
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Abstract

We describe a framework for building abstraction hierarchies whereby an agent alternates skill- and representation-construction phases to construct a sequence of increasingly abstract Markov decision processes. Our formulation builds on recent results showing that the appropriate abstract representation of a problem is specified by the agent's skills. We describe how such a hierarchy can be used for fast planning, and illustrate the construction of an appropriate hierarchy for the Taxi domain.

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使用技能-符号循环构造抽象层次结构。
我们描述了一个用于构建抽象层次结构的框架,通过该框架,智能体可以交替技能和表示构建阶段来构建一系列越来越抽象的马尔可夫决策过程。我们的公式建立在最近的结果之上,这些结果表明,问题的适当抽象表示是由代理的技能指定的。我们描述了如何将这种层次结构用于快速规划,并举例说明了出租车领域的适当层次结构的构造。
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