Abstract. Many autonomous agents operate in domains in which the cooperation of their fellow agents cannot be guaranteed. In such domains negotiation is essential to persuade others of the value of co-operation. This paper describes a general framework for negotiation in which agents exchange proposals backed by arguments which summarise the reasons why the proposals should be accepted. The argumentation is persuasive because the exchanges are able to alter the mental state of the agents involved. The framework is inspired by our work in the domain of business process management and is explained using examples from that domain. Keywords: Automated negotiation, Argumentation, Persuasion. 1

We propose a dialogue-game protocol of purchase negotiation dialogues which identifies appropriate speech acts, defines constraints on their utterances, and specifies the different sub-tasks agents need to perform in order to engage in dialogues according to this protocol. Our formalism combines a dialogue game from the philosophy of argumentation with a model of rational consumer purchase decision behaviour adopted from marketing theory. In addition to the dialogue formalism, we present a portfolio of decision mechanisms for the participating agents engaged in the dialogue and use these to provide our formalism with an operational semantics.

Abstract. In this paper we describe a language for reasoning about actions that can be used for modelling and for programming rational agents. We propose a modal approach for reasoning about dynamic domains in a logic programming setting. Agent behavior is specified by means of complex actions which are defined using modal inclusion axioms. The language is able to handle knowledge producing actions as well as actions which remove information. The problem of reasoning about complex actions with incomplete knowledge is tackled and the temporal projection and planning problems is addressed; more specifically, a goal directed proof procedure is defined, which allows agents to reason about complex actions and to generate conditional plans. We give a non-monotonic solution for the frame problem by making use of persistency assumptions in the context of an abductive characterization. The language has been used for implementing an adaptive web-based system.

We articulate a dialectical argumentation framework for qualitative representation of epistemic uncertainty in scientific domains. The framework is grounded in specific philosophies of science and theories of rational mutual discourse. We study the formal properties of our framework and provide it with a game theoretic semantics. With this semantics, we examine the relationship between the snaphots of the debate in the framework and the long run position of the debate, and prove a result directly analogous to the standard (Neyman-Pearson) approach to statistical hypothesis testing. We believe this formalism for representating uncertainty has value in domains with only limited knowledge, where experimental evidence is ambiguous or conflicting, or where agreement between different stakeholders on the quantification of uncertainty is difficult to achieve. All three of these conditions are found in assessments of carcinogenic risk for new chemicals.

The effectiveness of simulation-based training for individual tasks -- such as piloting skills -- is well established, but its use for team training raises challenging technical issues. Ideally, human users could gain valuable leadership experience by interacting with synthetic teammates in realistic and potentially stressful scenarios. However, creating human-like teammates that can support flexible, natural interactions with humans and other synthetic agents requires integrating a wide variety of capabilities, including models of teamwork, models of human negotiation, and the ability to participate in face-to-face spoken conversations in virtual worlds. We have developed such virtual humans by integrating and extending prior work in these areas, and we have applied our virtual humans to an example peacekeeping training scenario to guide and evaluate our research. Our models allow agents to reason about authority and responsibility for individual actions in a team task and, as appropriate, to carry out actions, give and accept orders, monitor task execution, and negotiate options. Negotiation is guided by the agents' dynamic assessment of alternative actions given the current scenario conditions, with the aim of guiding the human user towards an ability to make similar assessments.

Abstract. In this paper we describe an approach to the construction of adaptive tutoring systems, based on techniques from the research area of Reasoning about Actions and Change. This approach leads to the implementation of a prototype system, having a multi-agent architecture, whose kernel is a set of rational agents, programmed in the logic programming language DyLOG. In the prototype that we implemented the reasoning capabilities of the agents are exploited both to dynamically build study plans and to verify the correctness of user-given study plans with respect to the competence that the user wants to acquire.

There is currently a broad interest in dialogue acts and dialogue act taxonomies, and new uses, taxonomies, and standardization efforts continue to be proposed. This paper presents a discussion of issues that must be addressed in order to facilitate the shared understanding and use of taxonomies. The discussion is framed in terms of 20 questions, the answers to which will help make the meanings of taxonomy elements more clear to different communities of users.

An Agent Communication Language (ACL) is a collection of speech-act-like message types, with agreed-upon semantics, which facilitate the knowledge and information exchange between software agents.

Abstract. In open multi-agent systems agent interaction is usually ruled by public protocols defining the rules the agents should respect in message exchanging. The respect of such rules guarantees interoperability. Given two agents that agree on using a certain protocol for their interaction, a crucial issue (known as “a priori conformance test”) is verifying if their interaction policies, i.e. the programs that encode their communicative behavior, will actually produce interactions which are conformant to the agreed protocol. An issue that is not always made clear in the existing proposals for conformance tests is whether the test preserves agents’ capability of interacting, besides certifying the legality of their possible conversations. This work proposes an approach to the verification of a priori conformance, of an agent’s conversation policy to a protocol, which is based on the theory of formal languages. The conformance test is based on the acceptance of both the policy and the protocol by a special finite state automaton and it guarantees the interoperability of agents that are individually proved conformant. Many protocols used in multi-agent systems can be expressed as finite state automata, so this approach can be applied to a wide variety of cases with the proviso that both the protocol specification and the protocol implementation can be translated into finite state automata. In this sense the approach is general. Easy applicability to the case when a logic-based language is used to implement the policies is shown by means of a concrete example, in which the language DyLOG, based on computational logic, is used. 1

Jackal is a Java-based tool for communicating with the KQML agent communication language. Some features which make it extremely valuable to agent development are its conversation management facilities, exible, blackboard style interface and ease of integration. Jackal has been developed in support of an investigation of the use of agents in shop oor information ow. This paper describes Jackal at a surface and design level, and presents an example of its use in agent construction.