计划识别中的背景会计及其在交通监控中的应用
Accounting for Context in Plan Recognition, with Application to Traffic Monitoring
摘要：
典型的计划识别方法从代理人的可能计划的表示开始，并从代理人的行动的观察来评估各种候选人的可行性。一个更广泛的观点的任务（与一些以前的工作相一致）占的背景下，计划生成，代理的心理状态和规划过程，以及代理的行动在世界上的后果。我们提出了一个一般的贝叶斯框架，包括这一观点，并专注于如何上下文可以利用计划识别。我们演示的方法上的一个问题，在交通监控，其目标是诱导计划的司机从观察车辆的运动。从一个模型的驱动程序如何生成计划，我们展示了如何高速公路的上下文可以适当地影响识别器的解释所观察到的司机的行为。
英文摘要：
Typical approaches to plan recognition start from a representation of an agent's possible plans, and reason evidentially from observations of the agent's actions to assess the plausibility of the various candidates. A more expansive view of the task (consistent with some prior work) accounts for the context in which the plan was generated, the mental state and planning process of the agent, and consequences of the agent's actions in the world. We present a general Bayesian framework encompassing this view, and focus on how context can be exploited in plan recognition. We demonstrate the approach on a problem in traffic monitoring, where the objective is to induce the plan of the driver from observation of vehicle movements. Starting from a model of how the driver generates plans, we show how the highway context can appropriately influence the recognizer's interpretation of observed driver behavior.
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