This paper provides an overview of research and development activities in the field of autonomous agents and multi-agent systems. It aims to identify key concepts and applications, and to indicate how they relate to one-another. Some historical context to the field of agent-based computing is given, and contemporary research directions are presented. Finally, a range of open issues and future challenges are highlighted.

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

In a multi-agent environment, where self-motivated agents try to pursue their own goals, cooperation cannot be taken for granted. Cooperation must be planned for and achieved through communication and negotiation. We present a logical model of the mental states of the agents based on a representation of their beliefs, desires, intentions, and goals. We present argumentation as an iterative process emerging from exchanges among agents to persuade each other and bring about a change in intentions. We look at argumentation as a mechanism for achieving cooperation and agreements. Using categories identified from human multi-agent negotiation, we demonstrate how the logic can be used to specify argument formulation and evaluation. We also illustrate how the developed logic can be used to describe different types of agents. Furthermore, we present a general Automated Negotiation Agent which we implemented, based on the logical model. Using this system, a user can analyze and explore differe...

. Autonomous agents are designed to reach goals that were pre-defined by their operators. An important way to execute tasks and to maximize payoff is to share resources and to cooperate on task execution by creating coalitions of agents. Such coalitions will take place if, and only if, each member of a coalition gains more if he joins the coalition than he could gain before. There are several ways to create such coalitions and to divide the joint payoff among the members. Variance in these methods is due to different environments, different settings in a specific environment, and different approaches to a specific environment with specific settings. In this paper we focus on the cooperative (super-additive) environment, and suggest two different algorithms for coalition formation and payoff distribution in this environment. We also deal with the complexity of both computation and communication of each algorithm, and we try to give designers some basic tools for developing agents for th...

Artificial intelligence research falls roughly into two categories: formal and implementational. This division is not completely firm: there are implementational studies based on (formal or informal) theories (e.g., CYC, SOAR, OSCAR), and there are theories framed with an eye toward implementability (e.g., predicate circumscription). Nevertheless, formal /theoretical work tends to focus on very narrow problems (and even on very special cases of very narrow problems) while trying to get them "right" in a very strict sense, while implementational work tends to aim at fairly broad ranges of behavior but often at the expense of any kind of overall conceptually unifying framework that informs understanding. It is sometimes urged that this gap is intrinsic to the topic: intelligence is not a unitary thing for which there will be a unifying theory, but rather a "society" of subintelligences whose overall behavior cannot be reduced to useful characterizing and predictive principles.

This paper studies argumentation-based dialogues between agents. It defines a set of locutions by which agents can trade arguments, a set of agent attitudes which relate what arguments an agent can build and what locutions it can make, and a set of protocols by which dialogues can be carried out. The paper then considers some properties of dialogues under the protocols, in particular termination, dialogue outcomes, and complexity, and shows how these relate to the agent attitudes.

Cooperating and sharing resources by creating coalitions of agents are an important way for autonomous agents to execute tasks and to maximize payoff. Such coalitions will form only if each member of a coalition gains more if it joins the coalition than it could gain otherwise. There are several ways of creating such coalitions and dividing the joint payoff among the members. In this paper we present algorithms for coalition formation and payoff distribution in non-super-additive environments. We focus on a low-complexity kernel-oriented coalition formation algorithm. The properties of this algorithm were examined via simulations. These have shown that the model increases the benefits of the agents within a reasonable time period, and more coalition formations provide more benefits to the agents. Key Words Distributed AI, Coalition Formation, Multi-Agent Systems. This material is based upon work supported in part by the NSF under grant No. IRI-9423967, ARPA/Rome Labs contract F30602...

this paper, on how such a trait may be rendered in automated NLG.

To my parents, with love and gratitude. ii “What Should We Do? ” by Katie Atkinson The design and development of autonomous software agents requires a multitude of elements to be considered and accounted for. In order for a software agent to be con-sidered ‘intelligent ’ it must be able to perform effective reasoning about its beliefs and the environment in which it is situated, and also act in this environment. It must there-fore reason both about what is the case, and what should be done: the latter is known as practical reasoning. Additionally, it must also be able to interact and reason with other such agents in its environment, as it may rely on them for information and help to enable it to accomplish its tasks. This thesis is concerned with one particular as-pect of such agency: modelling the process of argument in practical reasoning to equip autonomous agents with the capability to determine the best action to take, in a given situation. The background setting for this work deals with the topic of practical reason-

Abstract. This paper presents some of the key techniques for reaching agreements in multi-agent environments. It discusses game-theory and economics based techniques: strategic negotiation, auctions, coalition formation, market-oriented programming and contracting. It also presents logical based mechanisms for argumentations. The focus of the survey is on negotiation of self-interested agents, but several mechanisms for cooperative agents who need to resolve conflicts that arise from conflicting beliefs about different aspects of their environment are also mentioned. For space reasons, we couldn’t cover all the relevant works, and the papers that are mentioned only demonstrate the possible approaches. We present some of the properties of the approaches using our own previous work. 1