Electronic markets, dispute resolution and negotiation protocols are three types of application domains that can be viewed as open agent societies. Key characteristics of such societies are agent heterogeneity, conflicting individual goals and unpredictable behaviour. Members of such societies 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 open agent societies. We adopt an external perspective and view societies as instances of normative systems. In this paper we demonstrate how the framework can be applied to specifying and executing a contract-net protocol. The specification is formalised in two action languages, the C+ language and the Event Calculus, and executed using respective software implementations, the Causal Calculator and the Society Visualiser. We evaluate our executable specification in the light of the presented case study, discussing the strengths and weaknesses of the employed action languages for the specification of open agent societies.

The majority of existing work on agent dialogues considers negotiation, persuasion or deliberation dialogues; we focus on inquiry dialogues, which allow agents to collaborate in order to find new knowledge. We present a general framework for representing dialogues and give the details necessary to generate two subtypes of inquiry dialogue that we define: argument inquiry dialogues allow two agents to share knowledge to jointly construct arguments; warrant inquiry dialogues allow two agents to share knowledge to jointly construct dialectical trees (essentially a tree with an argument at each node in which a child node is a counter argument to its parent). Existing inquiry dialogue systems only model dialogues, meaning they provide a protocol which dictates what the possible legal next moves are but not which of these moves to make. Our system not only includes a dialogue-game style protocol for each subtype of inquiry dialogue that we present, but also a strategy that selects exactly one of the legal moves to make. We propose a benchmark against which we compare our dialogues, being the arguments that can be constructed from the union of the agents ’ beliefs, and use this to define soundness and completeness properties that we show hold for all inquiry dialogues generated by our system.

Abstract One form of argument-based negotiation is when agents argue about why an offer was rejected. If an agent can state a reason for a rejection of an offer, the negotiation process may become more efficient since the other agent can take this reason into account when making new offers. Also, if a reason for rejection can be disputed, the negotiation process may be of higher quality since flawed reasons may be revised as a result. This paper presents a formal protocol for negotiation in which reasons can be asked and given for rejections and in which agents can try to persuade each other that a reason is or is not acceptable. The protocol is modelled as a persuasion dialogue game embedded in a negotiation protocol. It has a social semantics since the protocol does not refer to the internal state of negotiating agents. 1

This article presents a formal dialogue game for adjudication dialogues. Existing AI & law models of legal dialogues and argumentation-theoretic models of persuasion are extended with a neutral third party, to give a more realistic account of the adjudicator’s role in legal procedures. The main feature of the model is a division into a pleadings phase, where the adversaries plea their case and the adjudicator has a largely mediating role, and a decision phase, where the adjudicator decides the dispute on the basis of the claims, arguments and evidence put forward in the pleadings phase. The model allows for explicit decisions on admissibility of evidence and burden of proof by the adjudicator in the pleadings phase. Adjudication is modelled as putting forward arguments, in particular undercutting and priority arguments, in the decision phase. The model reconciles logical aspects of burden of proof induced by the defeasible nature of arguments with dialogical aspects of burden of proof as something that can be allocated by explicit decisions on legal grounds. 1

Abstract. Trust is a mechanism for managing the uncertainty about autonomous entities and the information they store, and so can play an important role in any decentralized system. As a result, trust has been widely studied in multiagent systems and related fields such as the semantic web. Managing information about trust involves inference with uncertain information, decision making, and dealing with commitments and the provenance of information, all areas to which systems of argumentation have been applied. Here we discuss the application of argumentation to reasoning about trust, identifying some of the components that an argumentation-based system for reasoning about trust would need to contain and sketching the work that would be required to provide such a system. 1

Abstract argumentation frameworks have played a major role as a way of understanding argumentbased inference, resulting in different argumentbased semantics. In order to make such semantics computationally attractive, suitable proof procedures are required, in which a search space of arguments is examined to find out which arguments are warranted or ultimately acceptable. This paper introduces a novel approach to model warrant computation in a skeptical abstract argumentation framework. We show that such search space can be defined as a lattice, and illustrate how the so-called dialectical constraints can play a role for guiding the efficient computation of warranted arguments. 1

Abstract. In this paper we describe PADUA, a protocol designed to enable agents

Argumentation is modelled as a game where the payoffs are measured in terms of the probability that the claimed conclusion is, or is not, defeasibly provable, given a history of arguments that have actually been exchanged, and given the probability of the factual premises. The probability of a conclusion is calculated using a standard variant of Defeasible Logic, in combination with standard probability calculus. It is a new element of the present approach that the exchange of arguments is analysed with game theoretical tools, yielding a prescriptive and to some extent even predictive account of the actual course of play. A brief comparison with existing argument-based dialogue approaches confirms that such a prescriptive account of the actual argumentation has been almost lacking in the approaches proposed so far.

Abstract. Norms represent what ought to be done, and their fulfillment can be seen as benefiting the overall system, society or organisation. However, individual agent goals (desire) may conflict with system norms. If a decision to comply with a norm is determined exclusively by an agent or, conversely, if norms are rigidly enforced, then system performance may be degraded, and individual agent goals may be inappropriately obstructed. To prevent such deleterious effects we propose a general framework for argumentation-based resolution of conflicts amongst desires and norms. In this framework, arguments for and against compliance are arguments justifying rewards, respectively punishments, exacted by ‘enforcing ’ agents. The arguments are evaluated in a recent extension to Dung’s abstract argumentation framework, in order that the agents can engage in metalevel argumentation as to whether the rewards and punishments have the required motivational force. We provide an example instantiation of the framework based on a logic programming formalism. 1

This paper presents a formal reconstruction of a Dutch civil legal case in Prakken’s formal model of adjudication dialogues. The object of formalisation is the argumentative speech acts exchanged during the dispute by the adversaries and the judge. The goal of this formalisation is twofold: to test whether AI & law models of legal dialogues in general, and Prakken’s model in particular, are suitable for modelling particular legal procedures; and to learn about the process of formalising an actual legal dispute.