Abstract: While the theoretical and experimental foundations of agent-based systems are becoming increasingly well understood, comparatively little effort has been devoted to understanding the everyday reality of carrying out an agent-based development project. As a result, agent system developers needlessly repeat the same mistakes. At best, this wastes resources; at worst, projects fail. The authors identify the main pitfalls awaiting the agent system developer and recommend ways to avoid or rectify them where possible.

Abstract: For sometime now agent-based and multi-agent systems (MASs) have attracted the interest of researchers far beyond traditional computer science and artificial intelligence (AI). In this article we try to identify focal points of interest for researchers working in the area of distributed AI (DAI) and MAS as well as application-oriented researchers coming from related disciplines, e.g. electrical and mechanical engineering. We do this by presenting key research topics in DAI and MAS research and by identifying application domains in which the DAI and MAS technologies are most suitable. The research topics we discuss are separated into agent architectures and organisations, negotiation among agents, and self-adaptation of MAS using learning techniques. Regarding the application domains for these techniques we distinguish the application domains according to whether the agents control a physical or virtual body (Gestalt) or not. This separation of the application domains is not strict; it represents two ends of a continuum. On the one end of this continuum we have autonomous robot systems which act in a physical environment (sometimes referred to as hardware agents), and on the other end, we have abstract environments, such as in workflow systems, which rarely display the geometrical and physical aspects of the environment we are used to living in.

Abstract: This paper describes an ongoing effort in developing a Multiagent System (MAS) for supply chain management. In our framework, functional agents can join in, stay, or leave the system. The Supply Chain Management System (SCMS) functionality is implemented through agent-based negotiation. When an order arrives, a virtual supply chain may emerge from the system through automated or semi-automated negotiation processes between functional agents. We present our framework and describe a number of negotiation performatives, which can be used to construct pair-wise and third party negotiation protocols for functional agent cooperation. We also explain how to formally model the negotiation process by using Colored Petri Nets (CPN) and we provide an example of establishing a virtual chain by solving a distributed constraint satisfaction problem.

Abstract: Fortunately, we are not the first to ask these questions, and researchers have already defined some helpful notions. First, authors have acknowledged that agents are entities within an environment, and that they can sense and act (not necessarily in that order). This means that agents are not isolated entities, and that they are able to communicate and collaborate with other entities. Simply put, agents that are not able to work together with other agents (humans included) are destined to become virtually useless.

Abstract: Despite the substantial number of multi-agent systems that use an Agent Communication Language (ACL) the dust has not settled yet over the landscape of ACLs. The semantic specification issues have monopolized the debate at the expense of other important pragmatic issues that must be adequately resolved in the immediate future if ACLs are going to support the development of robust agent systems. After introducing some of the basic concepts relating to Agent Communication Languages, we cover KQML and FIPA ACL, the two existing fully-specified ACLs. We give a brief introduction to their semantics and the issues relating to semantic descriptions of ACLs. We then shift our focus beyond the semantics and point to problems and limitations shared by both ACLs. Questions such as the nature of conformance of an agent system with an ACL specification and issues such as naming, registration, authentication, basic facilitation services, etc., may or may not be (technically speaking) part of an ACL specification, but we feel that the answers and solutions to such problems can 'make or break' an ACL. We finally discuss the future of ACL standardization efforts and identify the issues that are likely to emerge as we gain experience in building and deploying agent-based systems.

Abstract: In this paper it is shown how informal and formal specification of behavioural requirements and scenarios for agents and multi-agent systems can be integrated within multi-agent system design. In particular, it is addressed how a compositional perspective both on design descriptions and specification of behavioural requirements can be exploited. The approach has been applied in a case study: the development of a mediating information agent. It is shown that compositional verification benefits from the integration of requirements engineering within the design process.

Abstract: This article presents a new approach to the design of the architecture of a computer-integrated manufacturing (CIM) system. It starts with presenting the basic ideas of novel approaches which are best characterised as fractal or holonic models for the design of flexible manufacturing systems (FMS). The article discusses hierarchical and decentralised concepts for the design of such systems and argues that software agents are the ideal means for their implementation. The agent architecture InteRRaP for agent design is presented and is used to describe a planning and control architecture for a CIM system, which is separated into the layer of the production planning and control system, the shop floor control systems, the flexible cell control layer, the autonomous system layer, and the machine control layer. Two application scenarios are described at the end of the article and results are reported which were obtained from experiments with the implementations for these application scenarios. While one of these scenarios — a model of an FMS — is more research-oriented, the second one — optimisation of a production line — is directly related to an industrial real-world setting.

Abstract: The paper focuses on the design of multiagent systems and argues that traditional approaches fall short when dealing with complex multiagent systems. On this basis, this paper shows how an approach based on coordination models can help in the design of multiagent systems. A simple example in the area of conference management is assumed as a case study to clarify the concepts expressed.

Abstract: In recent years, electric utility industries worldwide have been undergoing deregulation to introduce competitiveness in the generation, transmission and distribution of electric power. The once centralised system planning and operation management must be remodelled to adapt to the new market structure. In particular, the trading mechanism needs to be totally revised as any party may now get involved in this free-market, subject to the unavoidable constraints such as generation volumes, physical transmission means and days-ahead scheduling. This paper presents a multi-agent model in conjunction with game theory to resolve the coalition formation for multilateral trades. The authors have implemented the model using the Java language and the JATLite/JAT0.3 agent development tools developed by Stanford University.

Abstract: A computational prototype of negotiation behavior is presented where the following occurs: (1) agents employ different concession matching tactics; (2) agents are unaware of opponent preferences; (3) agents incur a cost for delaying settlements; (4) agents vary in terms of goal difficulty and initial offer magnitude; and (5) demands and counter-offers are made and evaluated based on the opponent's degree of concession matching. This research explores the impact of the interaction of different agent behaviors on the negotiation process and the outcome of the negotiation. Simulation experiments show that the prototype is able to manifest fundamental patterns and confirms the effectiveness of classical negotiation and mediation strategies, such as ambitious goals and aggressive concession matching tactics. The model reveals some counterintuitive patterns that may shed a new perspective on the effects of time constraints and information availability.

Abstract: The objective of this paper is twofold In its first part, we survey the state of the art in research on agent architectures The architecture of an agent describes its modules and capabilities, and how these operate together We structure the field by investigating three important research threads, ie architectures for reactive agents, deliberative agents and interacting agents Then we describe various hybrid approaches that reconcile these three threads, aiming at a combination of different features like reactivity, deliberation and the ability to interact with other agents These approaches are contrasted with architectural issues of recent agent-based work, including software agents, softbots, believable agents, as well as commercial agent-based systems The second part of the paper addresses software engineers and system designers who are interested in applying agent technology to their problem domains The objective of this part is to assist these readers in deciding which agent architecture to choose for a specific application We characterise the most important domains to which the different approaches described in the first part have been applied, propose an application-related taxonomy of agents, and give a set of guidelines to select the right agent (architecture) for a given application

Abstract: We consider the problem of how to design large decentralized multi-agent systems (MAS's) in an automated fashion, with little or no hand-tuning. Our approach has each agent run a reinforcement learning algorithm. This converts the problem into one of how to automatically set/update the reward functions for each of the agents so that the global goal is achieved. In particular we do not want the agents to ``work at cross-purposes'' as far as the global goal is concerned. We use the term artificial COllective INtelligence (COIN) to refer to systems that embody solutions to this problem. In this paper we present a summary of a mathematical framework for COINs. We then investigate the real-world applicability of the core concepts of that framework via two computer experiments: we show that our COINs perform near optimally in a difficult variant of Arthur's bar problem (and in particular avoid the tragedy of the commons for that problem), and we also illustrate optimal performance for our COINs in the leader-follower problem.

Abstract: In this paper it is shown how informal and formal specification of behavioural requirements and scenarios for agents and multi-agent systems can be integrated within multi-agent system design. In particular, it is addressed how a compositional perspective both on design descriptions and specification of behavioural requirements can be exploited. The approach has been applied in a case study: the development of a mediating information agent. It is shown that compositional verification benefits from the integration of requirements engineering within the design process.

Abstract: This paper introduces a programming environment and architecture for the development of agent based cooperative applications using a role based approach. We focus on the cooperative aspects by introducing cooperation processes (CP) as a concept of its own. CPs describe all and only the coordination and cooperation parts of an application. The explicit documentation of the coordination and cooperation mechanisms used in a MAS allows their evaluation and reuse. We are able to change existing and introduce new cooperation processes at runtime without modifying the existing agents. We specify the cooperative behaviour of an agent in a separate role description. The interconnection of these roles constitutes the CP. Describing cooperation independent from concrete agents allows to build heterogeneous, federated and transformable MAS. We show how agents decide what roles to accept and how the agent-role interaction works. Finally we present the ROPE framework and runtime environment.

Abstract: Is it possible to make development of sophisticated agents simple enough to be practical? This article discusses the authors' theoretical and tool-creation efforts to answer that question in the affirmative. Building sophisticated agent-based systems of the future will require research advances on at least three fronts: we must continue work on agent theory so that many currently unanswered questions about the scope and limitations of alternative approaches to agent design can be addressed; we must make agent frameworks and infrastructure powerful, interoperable, and secure enough to support robust large-scale coordinated problem-solving activity; and we must develop new sorts of tools to help non-specialists unlock the power of agent technology.

Abstract: 1. Cooperating Distributed Grammar Systems 2. Parallel Communicating Grammar Systems 3. Eco-Grammar Systems and Colonies 4. Extensions to Non-Linear Structures 5. Applications

Abstract: Achieving effective cooperation in a multi-agent system is a difficult problem for a number of reasons such as limited and possibly out-dated views of activities of other agents and uncertainty about the outcomes of interacting non-local tasks. In this paper, we present a learning system called COLLAGE, that endows the agents with the capability to learn how to choose the most appropriate coordination strategy from a set of available coordination strategies. COLLAGE relies on meta-level information about agents' problem solving situations to guide them towards a suitable choice for a coordination strategy. We present empirical results that strongly indicate the effectiveness of the learning algorithm.

Abstract: Workflows are ubiquitous in business computing. They arise not only within an enterprise, but increasingly across enterprises as well—in situations such as virtual enterprises and applications such as supply-chain management. Although the importance of workflows as a basis for understanding and automating business activities is widely recognized, current workflow practice leaves much to be desired. To a large extent, this problem arises because of the rigidity of current technology, which does not accord well with the complex, heterogeneous, dynamic environments in which workflows are applied. Agent technology promises to alleviate many of these problems and hence enable adaptive workflows in realistic settings. We consider interaction-oriented programming (IOP), an approach to software engineering based on multiagent systems that we have been developing. We focus on one aspect of IOP, which deals with social commitments and enables agents to flexibly enact a multienterprise workflow by entering into and behaving according to their commitments to each other. The agents can cancel or modify their base-level commitments only if they satisfy the metacommitments that then go into effect.

Abstract: Principled negotiation coordinates the actions of agents with different interests, allowing distributed optimization. In principled negotiation, agents search for and propose options for mutual gain. If the other agents agree to the proposal, it is implemented. Under certain conditions, an agent can search for options for individual gain without impacting other agents. In these cases, the agent can negotiate with a coordinator, rather than obtain agreement from all other agents. The tenets of principled negotiation are outlined and stated mathematically. Two examples are formulated to test principled negotiation performance. The e rst has no coupling between the agent actions if coordination criteria are met. Principled negotiation allows the agents to achieve a solution as good as that achieved by a centralized controller with perfect knowledge. The second problem, based on the air trafe c management problem of negotiating arrival slots, is highly coupled, constraining each agent’ s available set of actions. Principled negotiation allows agents to search options that would not be available otherwise, improving the utility function of all agents. Applied to air trafe c operations, principled negotiation allows much greater freedom for optimization by system users while maintaining safety.

Abstract: A market-based algorithm is presented which autonomously apportions complex tasks to multiple cooperating agents giving each agent the motivation of improving performance of the whole system. A specific model, called “The Hayek Machine” is proposed and tested on a simulated Blocks World (BW) planning problem. Hayek learns to solve more complex BW problems than any previous learning algorithm. Given intermediate reward and simple features, it has learned to efficiently solve arbitrary BW problems. The Hayek Machine can also be seen as a model of evolutionary economics.

Abstract: Presents AGENDA (A GENeral testbed for Distributed AI Applications), a simulation tool developed for the simulation and design of applications involving interacting entities. This testbed consists of two different levels, the architecture level and the system development level. The architecture level describes a methodology for designing software agents by providing several important functionalities an agent should have. On the other hand, the system development level provides the basic knowledge representation formalism, general inference mechanisms, and a simulation tool-box supporting visualization and monitoring of agents. Following this, the applicability of AGENDA to the transportation domain is presented in detail. The main challenge of AGENDA in the context of this domain has been to provide different cooperation-scalable methods based on negotiation, leading to different scheduling mechanisms, and to experimentally evaluate these mechanisms. This evaluation shows that: (1) AGENDA is suitable for realistic application in the transportation domain; (2) the mechanisms used for vertical negotiation (between trucks considered as agents) and for horizontal negotiation (between companies considered as agents) are applicable for the real-world transportation domain applications. Finally, a complete study of the scalability of the simulation tool and the algorithms used for the negotiation is presented. This study, along with the evaluation of the different mechanisms, can help designers of transportation companies, particularly in the case of large companies.

Abstract: We present a multi-agent based approach for achieving cooperation between search systems employing different search paradigms. The search agents periodically interrupt their search, select interesting information from their states that is transmitted to the other agents, filter the information sent to them with respect to their own demands, integrate the remaining information into their search, and then continue the search. There are different kinds of information to be exchanged and the selection is both success- and demand-driven. We demonstrate the usefulness of this approach by coupling a search system based on a genetic algorithm and a branch-and-bound based system for job-shop-scheduling. Our experiments show that the cooperation results in finding better solutions within a given time limit and in finding solutions comparable to those generated by the best system working alone in less time. The speed-up factors for some examples even exceed the number of agents (computers) used.

Abstract: Metaglue is an extension to the Java programming language that provides very high-level support for writing groups of small software agents that interact with one another. Metaglue was developed as part of the AI Lab’s Intelligent Room Project. The Intelligent Room has literally dozens of hardware and software components that run on a variety of networked workstations. We needed a system that could link all of these components and coordinate the flow of data among them. The computational needs of the Intelligent Room -while not unique -were not satisfied by any pre-existing software systems or programming environments. We wanted the Intelligent Room’s software infrastructure to be persistent, robust, and dynamically reconfigurable. We needed the ability to modify (or even introduce) individual components without bringing the whole system down, and we wanted to have tools for understanding and debugging the behavior of large groups of interacting software agents. Thesis Supervisor: Tomás Lozano-Pérez Title: Associate Head, Computer Science

Abstract: Telecommunications infrastructures are a natural application domain for the distributed software agent paradigm. The authors clarify the potential application of software agent technology in legacy and future communications systems, and provide an overview of publicly available research on software agents used for communications management. The authors focus on the intelligent agent type of software agent, although the paper also reviews the reasons why mobile agents have made an impact in this domain. The author's objective is to describe some of the intricacies of using the software agent approach for the management of communications systems. The paper is in four main sections. The first section provides a brief introduction to software agent technology. The second section considers general problems of network management and the reasons why software agents may provide a suitable solution. The third section reviews some selected research on agents in a telecommunications management framework. The final section concludes the paper by discussing some of the problems encountered and some future directions for further research.

Abstract: Presents a distributed planning and control architecture for autonomous multi-manipulator systems (MMS). The control architecture is implemented using an agent-based approach. A team of distributed and autonomous agents is deployed to model the flexible assembly system in such a way that the agents negotiate, collaborate, and cooperate to achieve the goals of assembly tasks. The main focus of the paper is on assembly task allocation and assembly task execution. We describe the agent models and communication mechanism, and explain how they handle complex interactions among agents. A distributed trajectory planning approach based on artificial potential fields is also presented. Experimental results show that our multi-agent planning and control framework is suitable for flexible robotic assembly tasks. Our approach addresses the issues of flexibility, scalability, reconfigurability, and fault-tolerance. We anticipate that the same approach can be applied to other flexible manufacturing environments.

Abstract: One aspect of multi-agent systems (MAS) that has been only partially studied is their role in software engineering, and in particular their merit as a software architecture style. As we demonstrate, multi-agent systems developed to date have several common architectural characteristics, even though differences in their design and implementation result in variations in their strengths and weaknesses. A large portion of the research in the design and implementation of MAS addresses questions such as: given a computational problem—can one build a MAS to solve it? What should be the properties of this MAS given the problem? Having developed a MAS, what is the class of problems that this MAS, either as developed or with slight modifications, can solve? MAS research has provided several answers to the questions above. However, more fundamental questions were left un-answered: given a computational problem—is a MAS an appropriate solution? If it is, what type of MAS should be preferred? Asking these questions (and answering them) should precede the previous ones, lest multiagent systems may be designed and implemented where much simpler, more efficient solutions apply. In this report we provide analysis guidelines which—although do not explicitly answer these questions—support designers in their assessment of the suitability of MAS as a solution to computational problem they address. We discuss the architectural properties that should be considered when analyzing such systems and support our work with case-studies of several MAS.

Abstract: In multi-agent systems, most of the time, an agent does not have complete information about the preferences and decision making processes of other agents. This prevents even the cooperative agents from making coordinated choices, purely due to their ignorance of what other want. To overcome this problem, traditional coordination methods rely heavily on inter-agent communication, and thus become very inefficient when communication is costly or simply not desirable (e.g. to preserve privacy). In this paper, we propose the use of learning to complement communication in acquiring knowledge about other agents. We augment the communication-intensive negotiating agent architecture with a learning module, implemented as a Bayesian classifier. This allows our agents to incrementally update models of other agents' preferences from past negotiations with them. Based on these models, the agents can make sound predictions about others' preferences, thus reducing the need for communication in their future interactions.