基于Agent辩论谈判的奖励模型研究

电子商务谈判过程中,由于能使接受辩论的Agent根据它所接受到的辩论改变其偏好或目标,从而使谈判双方更快更好地达成一致,因而基于辩论的Agent谈判方式受到了广泛关注。目前已经有文献对此作了一定程度的研究,然而较少有对其中客观存在的威胁、奖励和申辩进行有效地形式化建模和描述。目标主要在于研究其中的奖励模型和其评价模型,然后在此基础上对奖励的评价模型进行模拟和分析,以评价其辩论力度的强弱,使被奖励对象最终做出正确选择。     

基于辩论的多agent商务谈判产生机制研究*

针对辩论的产生是基于辩论的谈判中agent决策机制的核心问题,提出了一个基于冲突解决和辩论分类的辩论产生机制,该机制包括谈判agent的多目标优化模型、谈判过程控制的状态机协议以及基于冲突解决的辩论生成策略等。最后通过一对一商务谈判原型系统验证了所提模型、协议和策略的有效性。     

用于辩证分析的多Agent辩论对话系统MAS-Arguing的设计与实现

多方对话博弈是当前多Agent辩论技术研究的难点.本文基于辩论理论的辩证语义,提出一种用于多方论据博弈的辩证分析模型DAM-MAG,并设计和实现了基于该模型的多Agent辩论对话系统MAS-Arguing,证明了DAM-MAG模型在技术上的可行性.为了多方对话博弈易于实现,MAS-Arguing引入辩论擂台管理Agent,负责协调和监控多个辩论Agent之间的角色转换和论据博弈.本文主要从体系结构、通信语言、多方对话协议和承诺规则等方面说明了MAS -Arguing系统的设计与实现.     

一种基于主体可信度的联合辩论框架

辩论框架是计算机利用辩论机制来解决实际问题的基础,如商务谈判、法律纠纷和劳动争议等。传统的辩论框架对辩论机制和论证方法作了具体的形式化描述,但忽略了辩论主体及其对辩论结果影响的描述,而且在辩论过程中一个论点通常需要多个论据的联合论证。针对以上问题,在传统辩论框架的基础上,提出了一种基于主体可信度的联合辩论框架(STUAF)。首先引入了辩论主体的概念,并对观点和论据之间的联合论证进行形式化定义;其次给出了完整的框架结构和语义描述,证明了该辩论框架满足Dunk提出的标准辩论框架的基本定理;然后结合辩论树给出了语义计算的算法;最后给出一个具体的应用实例,实例分析表明S I'UAF及其语义算法是有效的。     

辩论的理论模型及其算法研究

本文研究分布式人工智能背景下的辩论的理论模型及其算法,提出并建立了一个基于命题性知识的辩论的理论框架.在此框架下,我们给出了几个体现不同辩论策略的辩论算法,并对算法的正确性给出了理论证明.本文的研究可为分布式人工智能中多专家系统的辩论和意见综合提供参考,进一步的研究可望推进多专家联合系统的实用化进程.     

用于计算辩论的论据本体研究

近年来辩论技术在人工智能领域获得广泛关注。然而,在辩论过程中,如何高质高效地构建攻击论据仍然是难以解决的问题。通过分析论据的本质属性,形式定义论据的相关概念及相互关系,结构化论据的知识表示,实现了论据本体的建模。该论据本体的一致性和可用性通过一个辩论实例得以验证。在此基础上构建了一个原型系统,该系统能够在辩论过程中基于论据本体查找和构建论据,重用已构建的论据,从而有效提高了自动辩论的计算效率。     

Agent口碑辩论模型研究

基于辩论的Agent谈判能提高Agent在动态环境下的谈判效率,保证谈判效果。口碑则能强化辩论效果。为保证模型的整体性,将对Agent口碑辩论模型的阐述分为描述和评价两个部分;对口碑进行分类,结合形式化理论,提出Agent口碑辩论模型的描述部分;提出口碑辩论力度的概念,并对其进行量化,提出Agent口碑辩论模型的评价部分;最后通过算例对模型进行验证。     

基于可信度的辩论模型及争议评价算法

辩论是智能主体间为了消除分歧的一种基于言语的交互行为.由于知识的局限性,争议以及争议内部的陈述通常存在不确定性,因此在对辩论进行建模时需要考虑不确定信息处理问题.提出一种基于可信度的辩论模型（CFA）,该模型将争议表示为由若干前提和一个结论组成的可废止规则,并用对话树描述辩论推演过程.为了表示不确定性推理,引入可信度模型,将争议前提的不确定性和争议之间的攻击强度统一用可信度因子表示.在此基础上,提出计算陈述可信度的争议评价算法,并通过设定可信度阈值确定陈述的可接受性,得出最终辩论结果.最后,用一个实例说明该方法的有效性.该模型可以有效处理不确定信息条件下辩论推理过程,其辩论算法建立在数值计算基础之上,所得出的可接受陈述集在给定可信度阈值条件下是唯一的,可以克服Dung 的抽象辩论框架中扩充语义的不足.     

一种基于时态的扩展值辩论框架

时间是用来描述辩论过程以及辩论活动变化的一个重要因素,在辩论框架中加入时间因素是积极的。本文结合Dung的标准辩论框架以及Bench-Capon的基于值的辩论框架,提出了基于时态的扩展值辩论框架。首先分析了Dung的辩论框架以及Bench-Capon的值辩论框架在时态以及辩论值方面描述的局限性及需求,然后结合这些需求提出了基于时态的扩展值辩论框架,给出了完整的框架结构和语义描述,证明了基于时态的扩展值辩论框架满足Dung提出的标准辩论框架的一些基本定理。     

基于辩论的多商品谈判模型研究*

旨在对一组商品的多agent谈判进行研究,这组商品具有共同的性质,能满足买方特定需求。通过分析一组商品的属性特征,将商品的属性分为主属性和非主属性,用辩论方法构建多商品谈判机制,提出基于辩论的多商品谈判模型,并通过原型系统实验验证了模型的正确性和有效性。提出的模型将一组商品的多agent谈判统一到一个过程中,有利于达成谈判协议,提高谈判效率。     

Extending abstract argumentation systems theory

In this paper, we extend the theory of abstract argumentation systems proposed by Vreeswijk (1997). This framework stands at a high abstraction level and provides a general model for argumentation activity. However, the theory reveals an inherent limitation in that the premises of the argumentation process are assumed to be indefeasible, and this introduces the need of an implicit constraint on the strength of the arguments, in order to preserve correctness. In many application contexts the information available to start reasoning is not guaranteed to be completely reliable, therefore it is natural to assume that premises can be discarded during the argumentation process. We extend the theory by admitting that premises can be defeated and relaxing the implicit assumption about their strength.Besides fixing the technical problems related to this hidden assumption (e.g., ensuring that warranted arguments are compatible), our proposal provides an integrated model for belief revision and defeasible reasoning, confirming the suitability of argumentation as a general model for the activity of intelligent reasoning in presence of various kinds of uncertainty.     

A taxonomy of argumentation models used for knowledge representation

Understanding argumentation and its role in human reasoning has been a continuous subject of investigation for scholars from the ancient Greek philosophers to current researchers in philosophy, logic and artificial intelligence. In recent years, argumentation models have been used in different areas such as knowledge representation, explanation, proof elaboration, commonsense reasoning, logic programming, legal reasoning, decision making, and negotiation. However, these models address quite specific needs and there is need for a conceptual framework that would organize and compare existing argumentation-based models and methods. Such a framework would be very useful especially for researchers and practitioners who want to select appropriate argumentation models or techniques to be incorporated in new software systems with argumentation capabilities. In this paper, we propose such a conceptual framework, based on taxonomy of the most important argumentation models, approaches and systems found in the literature. This framework highlights the similarities and differences between these argumentation models. As an illustration of the practical use of this framework, we present a case study which shows how we used this framework to select and enrich an argumentation model in a knowledge acquisition project which aimed at representing argumentative knowledge contained in texts critiquing military courses of action.     

ANGLE: An autonomous, normative and guidable agent with changing knowledge

Some emerging computing systems (especially autonomic computing systems) raise several challenges to autonomous agents, including (1) how to reflect the dynamics of business requirements, (2) how to coordinate with external agents with sufficient level of security and predictability, and (3) how to perform reasoning with dynamic and incomplete knowledge, including both informational knowledge (observations) and motivational knowledge (for example, policy rules and contract rules). On the basis of defeasible logic and argumentation, this paper proposes an autonomous, normative and guidable agent model, called ANGLE, to cope with these challenges. This agent is established by combining beliefs-desires-intentions (BDI) architecture with policy-based method and the mechanism of contract-based coordination. Its architecture, knowledge representation, as well as reasoning and decision-making, are presented in this paper. ANGLE is characteristic of the following three aspects. First, both its motivational knowledge and informational knowledge are changeable, and allowed to be incomplete, inconsistent/conflicting. Second, its knowledge is represented in terms of extended defeasible logic with modal operators. Different from the existing defeasible theories, its theories (including belief theory, goal theory and intention theory) are dynamic (called dynamic theories), reflecting the variations of observations and external motivational knowledge. Third, its reasoning and decision-making are based on argumentation. Due to the dynamics of underlying theories, argument construction is not a monotonic process, which is different from the existing argumentation framework where arguments are constructed incrementally.     

基于论辩的Agent非单调推理

现有的Agent信念修正、慎思、手段-目的推理等理论和方法大多基于经典一阶逻辑,对不完全的、不一致的知识,缺乏有效的处理机制。基于论辩的Agent非单调推理(包括认识推理和实践推理)理论和方法有望弥补这个不足。不过,作为一个新的研究方向,其基本概念、理论、方法及存在的关键性问题尚有待于澄清和梳理。文中首先介绍论辩的基本概念。在此基础上,分析基于论辩的Agent非单调推理的最新研究进展。最后,讨论存在的关键性问题并指出可能的研究方向。     

Clear justification of modeling decisions for goal-oriented requirements engineering

Representation and reasoning about goals of an information system unavoidably involve the transformation of unclear stakeholder requirements into an instance of a goal model. If the requirements engineer does not justify why one clear form of requirements is chosen over others, the subsequent modeling decisions cannot be justified either. If arguments for clarification and modeling decisions are instead explicit, justifiably appropriate instances of goal models can be constructed and additional analyses applied to discover richer sets of requirements. The paper proposes the “Goal Argumentation Method (GAM)” to fulfil three roles: (i) GAM guides argumentation and justification of modeling choices during the construction or critique of goal model instances; (ii) it enables the detection of deficient argumentation within goal model instances; and (iii) it provides practical techniques for the engineer to ensure that requirements appearing both in arguments and in model instance elements are clear.

Dialectic proof procedures for assumption-based, admissible argumentation

We present a family of dialectic proof procedures for the admissibility semantics of assumption-based argumentation. These proof procedures are defined for any conventional logic formulated as a collection of inference rules and show how any such logic can be extended to a dialectic argumentation system.The proof procedures find a set of assumptions, to defend a given belief, by starting from an initial set of assumptions that supports an argument for the belief and adding defending assumptions incrementally to counter-attack all attacks.The proof procedures share the same notion of winning strategy for a dispute and differ only in the search strategy they use for finding it. The novelty of our approach lies mainly in its use of backward reasoning to construct arguments and potential arguments, and the fact that the proponent and opponent can attack one another before an argument is completed. The definition of winning strategy can be implemented directly as a non-deterministic program, whose search strategy implements the search for defences.     

Agents that argue and explain classifications

Argumentation is a promising approach used by autonomous agents for reasoning about inconsistent/incomplete/uncertain knowledge, based on the construction and the comparison of arguments. In this paper, we apply this approach to the classification problem, whose purpose is to construct from a set of training examples a model that assigns a class to any new example. We propose a formal argumentation-based model that constructs arguments in favor of each possible classification of an example, evaluates them, and determines among the conflicting arguments the acceptable ones. Finally, a “valid” classification of the example is suggested. Thus, not only the class of the example is given, but also the reasons behind that classification are provided to the user as well in a form that is easy to grasp. We show that such an argumentation-based approach for classification offers other advantages, like for instance classifying examples even when the set of training examples is inconsistent, and considering more general preference relations between hypotheses. In the particular case of concept learning, the results of version space theory developed by Mitchell are retrieved in an elegant way in our argumentation framework. Finally, we show that the model satisfies the rationality postulates identified in argumentation literature. This ensures that the model delivers sound results. This article extends and revises results presented in preliminary form in the paper [9].     

Encoding deductive argumentation in quantified Boolean formulae

There are a number of frameworks for modelling argumentation in logic. They incorporate a formal representation of individual arguments and techniques for comparing conflicting arguments. A common assumption for logic-based argumentation is that an argument is a pair 〈Φ,α〉 where Φ is minimal subset of the knowledge-base such that Φ is consistent and Φ entails the claim α. Different logics provide different definitions for consistency and entailment and hence give us different options for argumentation. Classical propositional logic is an appealing option for argumentation but the computational viability of generating an argument is an issue. To better explore this issue, we use quantified Boolean formulae to characterise an approach to argumentation based on classical logic.     

Artificial argument assistants for defeasible argumentation

The present paper discusses experimental argument assistance tools. In contrast with automated reasoning tools, the objective is not to replace reasoning, but to guide the user's production of arguments. Two systems are presented, and based on . The focus is on defeasible argumentation with an eye on the law. Argument assistants for defeasible argumentation naturally correspond to a view of the application of law as dialectical theory construction. The experiments provide insights into the design of argument assistants, and show the pros and cons of different ways of representing argumentative data. The development of the argumentation theories underlying the systems has culminated in the logical system that formalizes the interpretation of prima facie justified assumptions. introduces an innovative use of conditionals expressing support and attack. This allows the expression of warrants for support and attack, making it a transparent and flexible system of defeasible argumentation.