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

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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.

Traditional approaches to managing business processes are often inadequate for large-scale, organisation-wide, dynamic settings. However since Internet and Intranet technologies have become widespread, an increasing number of business processes exhibit these properties. Therefore a new approach is needed. To this end, we describe the motivation, conceptualisation, design and implementation of a novel agent-based business process management system. The key advance of our system is that responsibility for enacting various components of the business process is delegated to a number of autonomous problem solving agents. To enact their role, these agents typically interact and negotiate with other agents in order to coordinate their actions and to buy in the services they require. This approach leads to a system that is significantly more agile and robust than its traditional counterparts. To help demonstrate these benefits, a companion paper describes the application of our sys...

Auctions are the most widely used strategic gametheoretic mechanism in the Internet. Auctions have been mostly studied from a game-theoretic and economic perspective, although recent work in AI and OR has been concerned with computational aspects of auctions as well. When faced from a computational perspective, combinatorial auctions are perhaps the most challenging type of auctions. Combinatorial auctions are auctions where agents may submit bids for bundles of goods. Given that finding an optimal allocation of the goods in a combinatorial auction is intractable, researchers have been concerned with exposing tractable instances of combinatorial auctions.

Auctions provide an efficient way of resolving one-to-many negotiations. This is particularly true for automated agents where delays and long communications carry negative externalities. A properly designed auction, tailored to the specific needs of the relevant multi-agent system, can significantly improve its performance. In this paper, we focus on the specific problem of service allocation among autonomous, automated agents, within the context of the ADEPT project, which Z. concerns the BT British Telecom business process of providing a quote for designing a network for a customer. The main

While terminology and some concepts of behavior-based robotics have become widespread, the central ideas are often lost as researchers try to scale behavior to higher levels of complexity. "Hybrid systems" with model-based strategies that plan in terms of behaviors rather than simple actions have become common for higherlevel behavior. We claim that a strict behavior-based approach can scale to higher levels of complexity than many robotics researchers assume, and that the resulting systems are in many cases more efficient and robust than those that rely on "classical AI" deliberative approaches. Our focus is on systems of cooperative autonomous robots in dynamic environments. We will discuss both claims that deliberation and explicit communication are necessary to cooperation and systems that cooperate only through environmental interaction. In this context we introduce three design principles for complex cooperative behavior - minimalism, statelessness and tolerance - and present a ...

To be successful in open, multi-agent environments, autonomous agents must be capable of adapting their negotiation strategies and tactics to their prevailing circumstances. To this end, we present an empirical study showing the relative success of different strategies against different types of opponent in different environments. In particular, we adopt an evolutionary approach in which strategies and tactics correspond to the genetic material in a genetic algorithm. We conduct a series of experiments to determine the most successful strategies and to see how and when these strategies evolve depending on the context and negotiation stance of the agent's opponent. 1. Introduction Negotiation is a central component of many multi-agent systems. Agents negotiate to coordinate their activities and to come to mutually acceptable agreements about the division of labour and resources. In many cases, the agents involved are required to exhibit a range of different behaviours in a variety of ...

The design of social laws for artificial agent societies is a basic approach to coordinating multi-agent systems. It exposes the spectrum between fully-centralized and fully-decentralized coordination mechanisms. Useful social laws set constraints on the agents' activities which allow them to work individually in a mutually compatible manner.