Abstract argumentation systems

In this paper, we develop a theory of abstract argumentation systems. An abstract argumentation system is a collection of “defeasible proofs”, called arguments, that is partially ordered by a relation expressing the difference in conclusive force. The prefix “abstract” indicates that the theory is concerned neither with a specification of the underlying language, nor with the development of a subtheory that explains the partial order. An unstructured language, without logical connectives such as negation, makes arguments not (pairwise) inconsistent, but (groupwise) incompatible. Incompatibility and difference in conclusive force cause defeat among arguments. The aim of the theory is to find out which arguments eventually emerge undefeated. These arguments are considered to be in force. Several results are established. The main result is that arguments that are in force are precisely those that are in the limit of a so-called complete argumentation sequence.     

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.     

On the merging of Dung's argumentation systems

In this paper, the problem of deriving sensible information from a collection of argumentation systems coming from different agents is addressed. The underlying argumentation theory is Dung's one: each argumentation system gives both a set of arguments and the way they interact (i.e., attack or non-attack) according to the corresponding agent. The inadequacy of the simple, yet appealing, method which consists in voting on the agents' selected extensions calls for a new approach. To this purpose, a general framework for merging argumentation systems from Dung's theory of argumentation is presented. The objective is achieved through a three-step process: first, each argumentation system is expanded into a partial system over the set of all arguments considered by the group of agents (reflecting that some agents may easily ignore arguments pointed out by other agents, as well as how such arguments interact with her own ones); then, merging is used on the expanded systems as a way to solve the possible conflicts between them, and a set of argumentation systems which are as close as possible to the whole profile is generated; finally, voting is used on the selected extensions of the resulting systems so as to characterize the acceptable arguments at the group level.     

Formalizing value-guided argumentation for ethical systems design

The persuasiveness of an argument depends on the values promoted and demoted by the position defended. This idea, inspired by Perelman’s work on argumentation, has become a prominent theme in artificial intelligence research on argumentation since the work by Hafner and Berman on teleological reasoning in the law, and was further developed by Bench-Capon in his value-based argumentation frameworks. One theme in the study of value-guided argumentation is the comparison of values. Formal models involving value comparison typically use either qualitative or quantitative primitives. In this paper, techniques connecting qualitative and quantitative primitives recently developed for evidential argumentation are applied to value-guided argumentation. By developing the theoretical understanding of intelligent systems guided by embedded values, the paper is a step towards ethical systems design, much needed in these days of ever more pervasive AI techniques.     

Dynamics of argumentation systems: A division-based method

The changing of arguments and their attack relation is an intrinsic property of a variety of argumentation systems. So, it is very important to efficiently figure out how the status of arguments in a system evolves when the system is updated. However, unlike other areas of argumentation that have been deeply explored, such as argumentation semantics, proof theories, and algorithms, etc., dynamics of argumentation systems has been comparatively neglected. In this paper, we formulate a general theory (called a division-based method) to cope with this problem based on a new concept: the division of an argumentation framework. When an argumentation framework is updated, it is divided into three parts: an unaffected, an affected, and a conditioning part. The status of arguments in the unaffected sub-framework remains unchanged, while the status of the affected arguments is computed in a special argumentation framework (called a conditioned argumentation framework, or briefly CAF) that is composed of an affected part and a conditioning part. We have proved that under a certain semantics that satisfies the directionality criterion (complete, preferred, ideal, or grounded semantics), the extensions of the updated framework are equal to the result of a combination of the extensions of an unaffected sub-framework and sets of the extensions of a set of assigned CAFs. Due to the efficiency of the division-based method, it is expected to be very useful in various kinds of argumentation systems where arguments and attacks are dynamics.     

基于群体研讨支持系统的项目管理系统研究

项目管理在各行各业被广泛应用,目前市场上的项目管理软件虽然功能强大,但在实际的项目管理中常常不能得到很好的应用,甚至在某些项目中根本难以使用。首先考查当前项目管理软件的应用问题,提出了项目管理系统的需求。在此基础上,从项目管理过程、项目管理知识领域及项目利益相关人员三个角度抽象出项目管理框架,用来组织群体活动,并设计了基于群体研讨支持系统的项目管理信息系统,实现以项目利益相关人员为中心,对项目信息进行全方位的集成。并根据项目管理的信息需求,描述了该系统如何实现项目信息管理的需求。     

Organizational and behavioural issues raised by intelligent argumentation systems

This paper introduces and reviews intelligent argumentation systems. It seeks to define what such systems are, and to emphasize the crucial distinction between argument represenation and argument generation programs. Such a review includes both working programs and design ideas. The paper also explores some domain applications, suggesting the wide-ranging motivations which have stimulated the creation of such systems, and suggesting a model of roles which such systems play, such as critic and tutor. These roles have hitherto been almost wholly for individual decision support, and so the paper suggests some ways in which current roles can be generalized from individual to group support. Finally a model is put forward for answering questions such as: Where in an organization would such group systems fit? What is so different about such systems from other support systems? How do such systems relate to newly emerging organizational structures?     

Computer decision-support systems for public argumentation: assessing deliberative legitimacy

Recent proposals for computer-assisted argumentation have drawn on dialectical models of argumentation. When used to assist public policy planning, such systems also raise questions of political legitimacy. Drawing on deliberative democratic theory, we elaborate normative criteria for deliberative legitimacy and illustrate their use for assessing two argumentation systems. Full assessment of such systems requires experiments in which system designers draw on expertise from the social sciences and enter into the policy deliberation itself at the level of participants.

Computer-mediated communication: problems and potentials of argumentation support systems

Argumentation support systems have both advantages and disadvantages. For the individual, there is an increased power to express herself and to gain recognition and reward for the extra effort and frankness required, but at the cost of slowing down work, making the user constantly explain herself, and putting her statements at risk of being taken out of context. For the organisation, there is a gain in increased information sharing — the bane of current computer-mediated communication (CMC) systems — as the user is motivated to present relevant and convincing evidence to back up her statements, but at the cost of undermining ‘traditional' organisational structures and hierarchies.     

Practical reasoning as presumptive argumentation using action based alternating transition systems

In this paper we describe an approach to practical reasoning, reasoning about what it is best for a particular agent to do in a given situation, based on presumptive justifications of action through the instantiation of an argument scheme, which is then subject to examination through a series of critical questions. We identify three particular aspects of practical reasoning which distinguish it from theoretical reasoning. We next provide an argument scheme and an associated set of critical questions which is able to capture these features. In order that both the argument scheme and the critical questions can be given precise interpretations we use the semantic structure of an Action-Based Alternating Transition System as the basis for their definition. We then work through a detailed example to show how this approach to practical reasoning can be applied to a problem solving situation, and briefly describe some other previous applications of the general approach. In a second example we relate our account to the social laws paradigm for co-ordinating multi-agent systems. The contribution of the paper is to provide firm foundations for an approach to practical reasoning based on presumptive argument in terms of a well-known model for representing the effects of actions of a group of agents.     

Inductive inference and argumentation methods in modern intelligent decision support systems

Improvement of the classification quality for the generalization problem is considered. In order to improve the classification models produced by generalization algorithms, it is proposed to use argumentation methods based on defeasible reasoning with justification degrees. New methods and algorithms are proposed, and experimental results on various test data sets are described, including instances with noisy initial data.     

Abstract argumentation

In this paper we explore the thesis that the role of argumentation in practical reasoning in general and legal reasoning in particular is to justify the use of defeasible rules to derive a conclusion in preference to the use of other defeasible rules to derive a conflicting conclusion. The defeasibility of rules is expressed by means of non-provability claims as additional conditions of the rules.We outline an abstract approach to defeasible reasoning and argumentation which includes many existing formalisms, including default logic, extended logic programming, non-monotonic modal logic and auto-epistemic logic, as special cases. We show, in particular, that the admissibility semantics for all these formalisms has a natural argumentation-theoretic interpretation and proof procedure, which seem to correspond well with informal argumentation.In the admissibility semantics there is only one way for one argument to attack another, namely by undermining one of its non-provability claims. In this paper, we show how other kinds of attack between arguments, specifically how rebuttal and priority attacks, can be reduced to the undermining of non-provability claims.     

An application of formal argumentation: Fusing Bayesian networks in multi-agent systems

We consider a multi-agent system where each agent is equipped with a Bayesian network, and present an open framework for the agents to agree on a possible consensus network. The framework builds on formal argumentation, and unlike previous solutions on graphical consensus belief, it is sufficiently general to allow for a wide range of possible agreements to be identified.     

多Agent研讨平台的研究

研讨平台为群体决策者提供一个公共、开放的环境,可辅助解决各种重大复杂问题,但它的实现一直存在很多困难。现在,利用Agent自身所具有的特点,能有效地解决任务分布、组织机构的动态自组织等问题。根据研讨平台的自身需求,构造了研讨平台的系统结构,并定义了多个Agent角色及其功能,最后简单介绍了一个使用JADE实现的应用实例。