Logical models of argument formalize commonsense reasoning while taking process and computation seriously. This survey discusses the main ideas which characterize different logical models of argument. It presents the formal features of a few main approaches to the modeling of argumentation. We trace the

The work reported here introduces Defeasible Logic Programming (DeLP), a formalism that combines results of Logic Programming and Defeasible Argumentation. DeLP provides the possibility of representing information in the form of weak rules in a declarative manner, and a defeasible argumentation inference mechanism for warranting the entailed conclusions. In DeLP an argumentation formalism will be used for deciding between contradictory goals. Queries will be supported by arguments that could be defeated by other arguments. A query q will succeed when there is an argument A for q that is warranted, i. e. the argument A that supports q is found undefeated by a warrant procedure that implements a dialectical analysis. The defeasible argumentation basis of DeLP allows to build applications that deal with incomplete and contradictory information in dynamic domains. Thus, the resulting approach is suitable for representing agent’s knowledge and for providing an argumentation based reasoning mechanism to agents.

. This article investigates to what extent protocols for dynamic disputes, i.e., disputes in which the information base can vary at dierent stages, can be justied in terms of logics for defeasible argumentation. First a general framework is formulated for dialectical proof theories for such logics. Then this framework is adapted to serve as a framework for protocols for dynamic disputes, after which soundness and fairness properties are formulated for such protocols relative to dialectical proof theories. It then turns out that certain types of protocols that are perfectly ne with a static information base, are not sound or fair in a dynamic setting. Finally, a natural dynamic protocol is dened for which soundness and fairness can be established. 1. Introduction This paper studies the exchange of arguments and counterarguments in dynamic disputes, i.e., in disputes where the available information can change during the dispute. The research is motivated by two recent developments ...

. This paper presents dialectical proof theories for Dung's preferred semantics of defeasible argumentation. The proof theories have the form of argument games for testing membership of some (credulous reasoning) or all preferred extensions (sceptical reasoning). The credulous proof theory is for the general case, while the sceptical version is for the case where preferred semantics coincides with stable semantics. The development of these argument games is especially motivated by applications of argumentation in automated negotiation, mediation of collective discussion and decision making, and intelligent tutoring. 1 Introduction An important approach to the study of nonmonotonic reasoning is that of logics for defeasible argumentation (for an overview see [25]). Within this approach, a unifying perspective is provided by the work of [9] and [4] (below called the `BDKT framework'). It takes as input a set of arguments ordered by a binary relation of `attack', and it produces...

This article carries out a formal study of dialogue games for argumentation. A formal framework for such games is proposed which imposes an explicit reply structure on dialogues, where each dialogue move either attacks or surrenders to some earlier move of the other participant. The framework is flexible in several respects. It allows for different underlying logics, alternative sets of locutions and more or less strict rules for when they are allowed. In particular, it allows for varying degrees of coherence and flexibility when it comes to maintaining focus of a dialogue. Its formal nature supports the study of formal properties of specific dialogue protocols, especially on how they respect the underlying logic.

. This paper proposes a formal framework for argumentative dialogue systems with the possibility of counterargument. The framework allows for claiming, challenging, retracting and conceding propositions. It also allows for exchanging arguments and counterarguments for propositions, by incorporating argument games for nonmonotonic logics. A key element of the framework is a precise denition of the notion of relevance of a move, which enables exible yet well-behaved protocols. 1 Introduction In recent years, dialogue systems for argumentation have received interest in several elds of articial intelligence, such as explanation [2], AI and law [4, 6], discourse generation [5], multi-agent systems [10, 1], and intelligent tutoring [9]. These developments justify a formal study of such dialogue systems; this paper contributes to this study by an attempt to integrate two relevant developments in the elds of argumentation theory and articial intelligence. In argumentation theory...

This survey introduces existing approaches to agent communications languages (ACLs) and particularly, conversation policies (CPs) which can be viewed as general constraints on the sequence of semantically coherent messages leading to a goal. Then limitations of these CPs are discussed in detail, particularly limitations on flexibility and specification. Finally, ACLs are viewed from the dialectic point of view, and some approaches are introduced in this context: some focusing on commitment-based protocols and others on dialogue-game based protocols.

. This article surveys the use of logic in computational models of legal reasoning, against the background of a four-layered view on legal argument. This view comprises a logical layer (constructing an argument) ; a dialectical layer (comparing and assessing conicting arguments) ; a procedural layer (regulating the process of argumentation); and a strategic, or heuristic layer (arguing persuasively). Each further layer presupposes, and is built around the previous layers. At the rst two layers the information base is xed, while at the third and fourth layer it is constructed dynamically, during a dialogue or dispute. 1

In this work, we have been principally concerned with the representation of contracts so that their normative state may be tracked in an automated fashion over their deployment lifetime. The normative state of a contract, at a particular time, is the aggregation of instances of normative relations that hold between contract parties at that time, plus the current values of contract variables. The effects of contract events on the normative state of a contract are specified using an XML formalisation of the Event Calculus, called ecXML. We use an example mail service agreement from the domain of web services to ground the discussion of our work. We give a characterisation of the agreement according to the normative concepts of: obligation, power and permission, and show how the ecXML representation may be used to track the state of the agreement, according to a narrative of contract events. We also give a description of a state tracking architecture, and a contract deployment tool, both of which have been implemented in the course of our work. 1

Open multi-agent computational systems are composed of heterogeneous and possibly antagonistic software entities. Characteristic features are limited trust and unpredictable behaviour. Members of such systems may fail to, or even choose not to, conform to the norms governing their interactions. It has been argued that systems of this type should have a formal, declarative, verifiable, and meaningful semantics. We present a theoretical and computational framework being developed for the executable specification of such systems. We adopt an external perspective and view open computational systems as instances of normative systems. In this paper we demonstrate how the framework can be applied to specifying and executing an argumentation protocol based on Brewka’s reconstruction of Rescher’s theory of formal disputation. The specification is formalised in the action language C+ and executed using the ‘Causal Calculator’ (Ccalc) implementation.