摘要翻译：
本文发展了概率混合动作模型(PHAMs)，这是一种现实的因果模型，用于预测由现代感知驱动的机器人计划产生的行为。PHAMs代表了AI规划中大多数动作模型所不能代表的机器人行为的一些方面：连续控制过程的时间结构、它们的非确定性影响、它们的几种干扰模式，以及闭环机器人规划中触发条件的实现。本文的主要贡献是：（1）并发知觉驱动行为模型PHAMs的形式化，并证明了该模型可以产生定性准确的预测；（2）基于概率动作模型和状态描述的采样预测的PHAMs资源高效推理方法。基于分析和实验结果，我们展示了如何将PHAMs应用于规划一个自主机器人办公室快递员的行动过程。
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英文标题：
《Probabilistic Hybrid Action Models for Predicting Concurrent
  Percept-driven Robot Behavior》
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作者：
M. Beetz, H. Grosskreutz
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最新提交年份：
2011
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  This article develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predicting the behavior generated by modern percept-driven robot plans. PHAMs represent aspects of robot behavior that cannot be represented by most action models used in AI planning: the temporal structure of continuous control processes, their non-deterministic effects, several modes of their interferences, and the achievement of triggering conditions in closed-loop robot plans.   The main contributions of this article are: (1) PHAMs, a model of concurrent percept-driven behavior, its formalization, and proofs that the model generates probably, qualitatively accurate predictions; and (2) a resource-efficient inference method for PHAMs based on sampling projections from probabilistic action models and state descriptions. We show how PHAMs can be applied to planning the course of action of an autonomous robot office courier based on analytical and experimental results.
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PDF链接：
https://arxiv.org/pdf/1109.6030