目标操作的理性选择与目标驱动自治的集成ofSearch策略
The Rational Selection of Goal Operations and the Integration ofSearch Strategies with Goal-Driven Autonomy
摘要：
智能物理系统作为具体化的认知系统，必须执行高级推理，同时管理底层的控制架构。认知和控制之间的联系必须处理将连续值从现实世界转换到符号表征（和返回）的问题。为了产生有效的行为，推理必须包括重新计划、获取和更新新信息、检测和响应异常以及对系统目标执行各种操作的能力。但是，这些过程不是独立的，需要进一步的探索。本文研究了多目标操作同时发生并相互作用时Agent的选择问题，并建立了一种在多目标操作之间进行选择的方法。我们展示了好处，并讨论了权衡与此相关，并显示出积极的结果，在一个动态的海洋搜索任务。
英文摘要：
Intelligent physical systems as embodied cognitive systems must perform high-level reasoning while concurrently managing an underlying control architecture. The link between cognition and control must manage the problem of converting continuous values from the real world to symbolic representations (and back). To generate effective behaviors, reasoning must include a capacity to replan, acquire and update new information, detect and respond to anomalies, and perform various operations on system goals. But, these processes are not independent and need further exploration. This paper examines an agent's choices when multiple goal operations co-occur and interact, and it establishes a method of choosing between them. We demonstrate the benefits and discuss the trade offs involved with this and show positive results in a dynamic marine search task.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
