The Grid and agent communities both develop concepts and mechanisms for open distributed systems, albeit from different perspectives. The Grid community has historically focused on "brawn": infrastructure, tools, and applications for reliable and secure resource sharing within dynamic and geographically distributed virtual organizations. In contrast, the agents community has focused on "brain": autonomous problem solvers that can act flexibly in uncertain and dynamic environments. Yet as the scale and ambition of both Grid and agent deployments increase, we see a convergence of interests, with agent systems requiring robust infrastructure and Grid systems requiring autonomous, flexible behaviors. Motivated by this convergence of interests, we review the current state of the art in both areas, review the challenges that concern the two communities, and propose research and technology development activities that can allow for mutually supportive efforts.

In the last few years we have witnessed a surge of business-to-consumer and business-to-business commerce operated on the Internet. However, most current electronic commerce systems are little more than electronic catalogues that allow a user to purchase a product under predetermined and inflexible terms and conditions. We believe that in the next few years we will see a new generation of electronic commerce systems emerge, based on automated negotiation. In this paper, we identify the main parameters on which any automated negotiation depends. To show the applicability of our classification framework, we use it to categorise a representative sample of some of the most prominent negotiation models that exist in the literature.

Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular,

Automated negotiation is a key form of interaction in systems that are composed of multiple autonomous agents. The aim of such interactions is to reach agreements through an iterative process of making offers. The content of such proposals are, however, a function of the strategy of the agents. Here we present a strategy called the trade-off strategy where multiple negotiation decision variables are traded-off against one another (e.g., paying a higher price in order to obtain an earlier delivery date or waiting longer in order to obtain a higher quality service). Such a strategy is commonly known to increase the social welfare of agents. Yet, to date, most computational work in this area has ignored the issue of trade-offs, instead aiming to increase social welfare through mechanism design. The aim of this paper is to develop a heuristic computational model of the trade-off strategy and show that it can lead to an increased social welfare of the system. A novel linear algorithm is presented that enables software agents to make trade-offs for multi-dimensional goods for the problem of distributed resource allocation.

Designers of agent communications protocols are increasingly using formal dialogue games, adopted from argumentation theory, as the basis for structured agent interactions. We propose a set of desiderata for such protocols, drawing on recent research in agent interaction, on recent criteria for assessment of automated auction mechanisms and on elements of argumentation theory and political science. We then assess several recent dialogue game protocols against our desiderata, revealing that each protocol has serious weaknesses. For comparison, we also assess the FIPA Agent Communications Language (ACL), thereby showing FIPA ACL to have limited applicability to dialogues not involving purchase negotiations. We conclude with a suggested checklist for designers of dialogue game protocols for agent interactions.

Negotiation is essential in settings where autonomous agents have conflicting interests and a desire to cooperate. For this reason, mechanisms in which agents exchange potential agreements according to various rules of interaction have become very popular in recent years as evident, for example, in the auction and mechanism design community. However, a growing body of research is now emerging which points out limitations in such mechanisms and advocates the idea that agents can increase the likelihood and quality of an agreement by exchanging arguments which influence each others ’ states. This community further argues that argument exchange is sometimes essential when various assumptions about agent rationality cannot be satisfied. To this end, in this article, we identify the main research motivations and ambitions behind work in the field. We then provide a conceptual framework through which we outline the core elements and features required by agents engaged in argumentation-based negotiation, as well as the environment that hosts these agents. For each of these elements, we survey and evaluate existing proposed techniques in the literature and highlight the major challenges that need to be addressed if argument-based negotiation research is to reach its full potential.

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.

This paper analyzes the process of automated negotiation between two competitive agents that have firm deadlines and incomplete information about their opponent. Generally speaking, the outcome of a negotiation depends on many parameters---including the agents' preferences, their reservation limits, their attitude toward time and the strategies they use. Although in most realistic situations it is not possible for agents to have complete information about each of these parameters for its opponent, it is not uncommon for agents to have partial information about some of them. Under such uncertainty, our aim is to determine how an agent can exploit its available information to select an optimal strategy.

This paper develops a fuzzy constraint based model for bilateral multi-issue negotiation in trading environments. In particular, we are concerned with the principled negotiation approach in which agents seek to strike a fair deal for both parties, but which, nevertheless, maximises their own payoff. Thus, there are elements of both competition and cooperation in the negotiation (hence semi-competitive environments) . One of the key intuitions of the approach is that there is often more than one option that can satisfy the interests of both parties. So, if the opponent cannot accept an offer then the proponent should endeavour to find an alternative that is equally acceptable to it, but more acceptable to the opponent. That is, the agent should make a trade-off. Only if such a trade-off is not possible should the agent make a concession. Against this background, our model ensures the agents reach a deal that is fair (Pareto-optimal) for both parties if such a solution exists. Moreover, this is achieved by minimising the amount of private information that is revealed. The model uses prioritised fuzzy constraints to represent trade-offs between the different possible values of the negotiation issues and to indicate how concessions should be made when they are necessary. Also by using constraints to express negotiation proposals, the model can cover the negotiation space more ef- ficiently since each exchange covers a region rather than a single point (which is what most existing models deal with). In addition, by incorporating the notion of a reward into our negotiation model, the agents can sometimes reach agreements that would not otherwise be possible.

Global communication networks and advances in information technology enable the design of information systems facilitating effective formulation and efficient resolution of negotiation problems. Increasingly, these systems guide negotiators in clarifying the relevant issues, provide media for offer formulation and exchange, and help in achieving an agreement. In practice, the task of analysing, modelling, designing and implementing electronic negotiation media demands a systematic, traceable and reproducible approach. An engineering approach to media specification and construction has these characteristics. In this paper, we provide a rationale for the engineering approach that allows pragmatic adoption of economic and social sciences perspectives on negotiated decisions for the purpose of supporting and undertaking electronic negotiations. Similarities and differences of different theories that underlie on-going studies of electronic negotiations are identified. This provides a basis for integration of different theories and approaches for the specific purpose of the design of effective electronic negotiations. Drawing on diverse streams of literature in different fields such as economics, management, computer, and behavioural sciences, we present an example of an integration of three significant streams of theoretical and applied research involving negotiations, traditional auctions and on-line auctions.