基于情境演算的智能体结构

Agent结构的建立是Agent研究的重要内容.尝试着结合BDI结构和情境演算的优点,提出了一个能够刻画Agent的多种特征,尤其是自主性的智能体结构AASC(Agent architecture based on situation calculus).此结构既能表示Agent的信念、目标、策略等心智状态,又能进行行动推理和规划,为解释Agent的自主性、建构不同类型的Agent提供了统一的平台.     

Causality and Counterfactuals in the Situation Calculus

Structural causal models offer a popular framework for exploringcausal concepts. However, due to their limited expressiveness,structural models have difficulties coping with such conceptsas actual (event-to-event) causation. In this article, we proposea new type of causal model, based on embedding structural considerationsin the language of situation calculus. By using situation calculusas a basic language, we leverage its power to express complex,dynamically changing situations and, by relying on structuralconsiderations, we can formulate an effective theory of counterfactualswithin the situation-calculus.     

Non-Markovian control in the Situation Calculus

In reasoning about actions, it is commonly assumed that the dynamics of domains satisfies the Markov Property: the executability conditions and the effects of all actions are fully determined by the present state of the system. This is true in particular in Reiter's Basic Action Theories in the Situation Calculus. In this paper, we generalize Basic Action Theories by removing the Markov property restriction, making it possible to directly axiomatize actions whose effects and executability conditions may depend on past and even alternative, hypothetical situations. We then generalize Reiter's regression operator, which is the main computational mechanism used for reasoning with Basic Action Theories, so that it can be used with non-Markovian theories.     

Goal Change in the Situation Calculus

Although there has been much discussion of belief change (e.g.[4, 21]), goal change has not received much attention. In thispaper, we propose a method for goal change in the frameworkof Reiter's; [12] theory of action in the situation calculus[8, 10], and investigate its properties. We extend the frameworkdeveloped by Shapiro et al. [17] and Shapiro and Lespérance[16], where goals and goal expansion were modelled, but goalcontraction was not.     

Iterated belief change in the situation calculus

John McCarthy's situation calculus has left an enduring mark on artificial intelligence research. This simple yet elegant formalism for modelling and reasoning about dynamic systems is still in common use more than forty years since it was first proposed. The ability to reason about action and change has long been considered a necessary component for any intelligent system. The situation calculus and its numerous extensions as well as the many competing proposals that it has inspired deal with this problem to some extent. In this paper, we offer a new approach to belief change associated with performing actions that addresses some of the shortcomings of these approaches. In particular, our approach is based on a well-developed theory of action in the situation calculus extended to deal with belief. Moreover, by augmenting this approach with a notion of plausibility over situations, our account handles nested belief, belief introspection, mistaken belief, and handles belief revision and belief update together with iterated belief change.     

Event calculus and temporal action logics compared

We compare the event calculus and temporal action logics (TAL), two formalisms for reasoning about action and change. We prove that, if the formalisms are restricted to integer time, inertial fluents, and relational fluents, and if TAL action type specifications are restricted to definite reassignment of a single fluent, then the formalisms are not equivalent. We argue that equivalence cannot be restored by using more general TAL action type specifications. We prove however that, if the formalisms are further restricted to single-step actions, then they are logically equivalent.     

A New Method for Reasoning about Action

Reasoning about action is an important aspect of common sense reasoning and planning.It gives rise to three classical problems:the frame problem,the qualification problem and the ramification problem.Existing approaches cannot deal with these problems efficiently.This paper presents a new method which uses the stratified ATMS for reasoning about action to overcome the limitations of these approaches.     

OSC:一个开放式情景演算系统的研究

在经典情景演算系统的基础上引入了广义信念修正理论，构建了一个开放式情景演算系统OSC(open situation calculus)，克服了经典情景演算系统不能刻画交互通信能力以及对事件的响应处理能力的缺陷．OSC系统保留了经典情景演算系统中的情景流result-of(a，s)，用以刻画行动的影响；同时又引入了新的情景流bel-rev(φ，s)，用以刻画通信交互以及对事件的响应处理等具有开放性信息的活动．OSC系统采用了离线规划与在线执行相结合的运行方式，为面向agent程序设计语言、面向agent智能系统的设计开发等应用提供了有效途径．     

FLUX中负析取约束的研究与实现*

FLUX是基于流演算的逻辑程序语言,实现agents在不完全状态下对其动作和感知信息进行逻辑推理。FLUX利用不同的约束来编码不完全状态,但现有的约束并不能覆盖所有流演算状态公式,这势必影响FLUX的应用范围。针对以上问题,在FLUX中引入负析取约束,利用约束处理规则集（CHRs）加以实现,并基于流演算基础语义分析了负析取约束的正确性,从而提高了FLUX对不完全状态的表达能力。     

TEMPORAL REASONING WITH THE MODAL LOGIC Z

This article presents a formal theory of concurrent actions that handles the qualification, ramification, and frame problems. The theory is capable of temporal explanation, i.e., reasoning forward and backward. The approach uses the modal logic Z to extend the work of Lifschitz and Rabinov on miracle-based temporal reasoning. The advantages of miracles for describing unknown actions are augmented with the ability to handle concurrent actions that can provide for the most economical explanation of state changes. For temporal explanation problems restricted to finite domains, it has a worst-case exponential decision procedure. The theory is as general as first-order logic in what it can express as preconditions and consequences of actions.     

A causal approach to nonmonotonic reasoning

We introduce logical formalisms of production and causal inference relations based on input/output logics of Makinson and Van der Torre [J. Philos. Logic 29 (2000) 383–408]. These inference relations will be assigned, however, both standard semantics (giving interpretation to their rules), and natural nonmonotonic semantics based on the principle of explanation closure. The resulting nonmonotonic formalisms will be shown to provide a logical representation of abductive reasoning, and a complete characterization of causal nonmonotonic reasoning from McCain and Turner [Proc. AAAI-97, Providence, RI, 1997, pp. 460–465]. The results of the study suggest production and causal inference as general nonmonotonic formalisms providing an alternative representation for a significant part of nonmonotonic reasoning.     

基于流演算的智能虚拟人模型研究与实现*

在研究流演算理论及其实现语言FLUX的基础上,将流演算与虚拟现实技术中的虚拟人相结合,提出了一个基于目标驱动的、有自主行动能力的虚拟人模型。设计了动作检测模块,同时使用了动作队列,根据动作检测的结果来决定是否执行下一个动作,使虚拟人可以针对动态变化的虚拟环境进行有效的行动规划。利用此模型可以快速构建出一个在不完全可知的虚拟环境中通过感知到的有限信息进行实时的、自主行动推理的智能虚拟人。最后,实现了办公室场景中智能虚拟人行动推理系统。     

事件演算在行动推理中的应用

事件演算是基于一阶谓词演算的行动推理理论.它可作为描述事件的一个工具,在行动推理的应用中显示出其强大的表示能力和实现能力.在事件演算中,可以对行动进行公理化,可以描述行动的时间性、并发性、连续变化及知识,而且还可用Prolog实现.讨论介绍与这些应用相关的基本概念、思想和方法等,并且通过一个送咖啡的例子说明了如何通过事件演算来描述和实现.     

A semantic characterization of a useful fragment of the situation calculus with knowledge

The situation calculus, as proposed by McCarthy and Hayes, and developed over the last decade by Reiter and co-workers, is reconsidered. A new logical variant called ES is proposed that captures much of the expressive power of the original, but where certain technical results are much more easily proved. This is illustrated using two existing non-trivial results: the determinacy of knowledge theorem of Reiter and the regression theorem, which reduces reasoning about the future to reasoning about the initial situation. Furthermore, we show the correctness of our approach by embedding ES in Reiter's situation calculus.