ABSTRACT

Goal-driven autonomy is an agent model for managing a dynamic environment by reasoning about current and potential goals while planning and acting. Since unexpected events and conditions may cause an agent’s goals and plans to become invalid or infeasible, an agent with goal-driven autonomy should monitor the environment against its expectations. Designed for dynamic, open, and partially observable environments, such an agent can create new goals or change its existing goals as needed. We present a formalisation of expectations for agents operating in these kinds of environments. Our formalisation includes situations where agents have the capability to sense the environment with some associated costs. We examine agent choices and behaviour in these domains and evaluate multiple approaches for selecting a subset of the agent’s sensing actions to execute. The contributions of this work are (1) a specification of different approaches to generating expectations; (2) a formalisation of the autonomy problem that minimises sensing costs; (3) a complexity analysis of the problem; (4) new algorithms for deciding which sensing actions to perform; and (5) empirical results demonstrating the benefit and cost of these approaches.

摘要

目标驱动的自治是一种代理模型，用于通过在计划和行动时推理当前和潜在目标来管理动态环境。由于意外事件和条件可能导致代理的目标和计划无效或不可行，因此具有目标驱动自主性的代理应根据其预期监控环境。专为动态、开放和部分可观察的环境而设计，此类代理可以根据需要创建新目标或更改其现有目标。我们提出了对在这些环境中运行的代理的期望的形式化。我们的形式化包括代理有能力感知环境并产生一些相关成本的情况。我们检查了这些领域中的代理选择和行为，并评估了多种方法来选择要执行的代理感知动作的子集。这项工作的贡献是（1）对产生期望的不同方法的规范；(2) 最小化感知成本的自治问题的形式化；(3) 问题的复杂性分析；(4) 决定执行哪些传感动作的新算法；(5) 实证结果证明了这些方法的收益和成本。