Showing papers on "Multi-agent system published in 1997"

Agent-based software engineering

Abstract: The technology of intelligent agents and multi-agent systems is expected to alter radically the way in which complex, distributed, open systems are conceptualised and implemented. The paper considers the problem of building a multi-agent system as a software engineering enterprise. Three issues are focused on: how agents might be specified; how these specifications might be refined or otherwise transformed into efficient implementations: and how implemented agents and multi-agent systems might subsequently be verified, to show that they are correct with respect to their specifications. These issues are discussed with reference to a number of case studies. The paper concludes by setting out some issues and open problems for future research.

"Go to the ant": Engineering principles from natural multi-agent systems

Abstract: Agent architectures need to organize themselves and adapt dynamically to changing circumstances without top-down control from a system operator. Some researchers provide this capability with complex agents that emulate human intelligence and reason explicitly about their coordination, reintroducing many of the problems of complex system design and implementation that motivated increasing software localization in the first place. Naturally occurring systems of simple agents (such as populations of insects or other animals) suggest that this retreat is not necessary. This paper summarizes several studies of such systems, and derives from them a set of general principles that artificial multi-agent systems can use to support overall system behavior significantly more complex than the behavior of the individuals agents.

Reinforcement learning in the multi-robot domain

Abstract: This paper describes a formulation of reinforcement learning that enables learning in noisy, dynamic environments such as in the complex concurrent multi-robot learning domain. The methodology involves minimizing the learning space through the use of behaviors and conditions, and dealing with the credit assignment problem through shaped reinforcement in the form of heterogeneous reinforcement functions and progress estimators. We experimentally validate the approach on a group of four mobile robots learning a foraging task.

DESIRE: Modelling Multi-Agent Systems in a Compositional Formal Framework

Abstract: This paper discusses an example of the application of a high-level modelling framework which supports both the specification and implementation of a system's conceptual design. This framework, DESIRE (framework for DEsign and Specification of Interacting REasoning components), explicitly models the knowledge, interaction, and coordination of complex tasks and reasoning capabilities in agent systems. For the application domain addressed in this paper, an operational multi-agent system which manages an electricity transportation network for a Spanish electricity utility, a comprehensible specification is presented.

Analysis and Design of Multiagent Systems Using MAS-Common KADS

Abstract: This article proposes an agent-oriented methodology called MAS-CommonKADS and develops a case study. This methodology extends the knowledge engineering methodology CommonKADS with techniques from objectoriented and protocol engineering methodologies. The methodology consists of the development of seven models: Agent Model, that describes the characteristics of each agent; Task Model, that describes the tasks that the agents carry out; Expertise Model, that describes the knowledge needed by the agents to achieve their goals; Organisation Model, that describes the structural relationships between agents (software agents and/or human agents); Coordination Model, that describes the dynamic relationships between software agents; Communication Model, that describes the dynamic relationships between human agents and their respective personal assistant software agents; and Design Model, that refines the previous models and determines the most suitable agent architecture for each agent, and the requirements of the agent network.

Layered learning in multiagent systems

Abstract: Multi-agent systems in complex, real-time domains require agents to act effectively both autonomously and as part of a team. This dissertation addresses multi-agent systems consisting of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. Because of the inherent complexity of this type of multi-agent system, this thesis investigates the use of machine learning within multi-agent systems. The dissertation makes four main contributions to the fields of Machine Learning and Multi-Agent Systems. First, the thesis defines a team member agent architecture within which a flexible team structure is presented, allowing agents to decompose the task space into flexible roles and allowing them to smoothly switch roles while acting. Team organization is achieved by the introduction of a locker-room agreement as a collection of conventions followed by all team members. It defines agent roles, team formations, and pre-compiled multi-agent plans. In addition, the team member agent architecture includes a communication paradigm for domains with single-channel, low-bandwidth, unreliable communication. The communication paradigm facilitates team coordination while being robust to lost messages and active interference from opponents. Second, the thesis introduces layered learning, a general-purpose machine learning paradigm for complex domains in which learning a mapping directly from agents' sensors to their actuators is intractable. Given a hierarchical task decomposition, layered learning allows for learning at each level of the hierarchy, with learning at each level directly affecting learning at the next higher level. Third, the thesis introduces a new multi-agent reinforcement learning algorithm, namely team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL is designed for domains in which agents cannot necessarily observe the state changes when other team members act. It exploits local, action-dependent features to aggressively generalize its input representation for learning and partitions the task among the agents, allowing them to simultaneously learn collaborative policies by observing the long-term effects of their actions. Fourth, the thesis contributes a fully functioning multi-agent system that incorporates learning in a real-time, noisy domain with teammates and adversaries. Detailed algorithmic descriptions of the agents' behaviors as well as their source code are included in the thesis. Empirical results validate all four contributions within the simulated robotic soccer domain. The generality of the contributions is verified by applying them to the real robotic soccer, and network routing domains. Ultimately, this dissertation demonstrates that by learning portions of their cognitive processes, selectively communicating, and coordinating their behaviors via common knowledge, a group of independent agents can work towards a common goal in a complex, real-time, noisy, collaborative, and adversarial environment.

Application of multi-agent systems in traffic and transportation

Abstract: Agent-oriented techniques offer a new approach to support the whole software development process. All the phases in the software development process are treated with a single uniform concept, namely that of agents, and a system modelled by a collection of agents is called a multi-agent system. AOTs as a new advance in information technology can help to respond to the growing interest in making traffic and transportation more efficient, resource-saving and ecological. The authors give an overview of a diverse range of applications where multi-agent systems promise to create a great impact in this domain. To demonstrate the ideas behind AOTs and their applicability in this domain, two applications under development at Daimler-Benz Research are described in some detail.

Challenger: a multi-agent system for distributed resource allocation

Abstract: In this paper we introduce Challenger, a multiagent system that performs completely distributed resource allocation. Challenger consists of agents which individually manage local resources; these agents communicate with one another to share their resources (in this particular instance, CPU time) in an attempt to more e ciently utilize them. By endowing the agents with relatively simple behaviors which rely on only locally available information, desirable global system objectives can be obtained, such as minimization of mean job ow time. Challenger is similar to other market-based control systems in that the agents act as buyers and sellers in a marketplace, always trying to maximize their own utility. The results of several simulations of Challenger performing CPU load balancing in a network of computers are presented. The main contribution of this research is the addition of learning to the agents, which allows Challenger to perform better under a wider range of conditions than other systems for distributed processor allocation, such as Malone's Enterprise [Mal88].

On cooperation in multi-agent systems

Abstract: Cooperation is often presented as one of the key concepts which differentiates multi-agent systems from other related disciplines such as distributed computing, object-oriented systems, and expert systems. However, it is a concept whose precise usage in agent-based systems is at best unclear and at worst highly inconsistent. Given the centrality of the issue, and the different ideological viewpoints on the subject, this was a lively panel which dealt with the following main issues.

SIMPOP: a multiagent system for the study of urbanism

Abstract: SIMPOP is a knowledge-based simulation system for the description of the evolution of settlement patterns over long time periods. Rules and parameters are introduced into a multiagent systems formalism where each settlement is considered as a separate entity interacting with the others and transforming itself. The rules may allow for the simulation of the ‘urban transition’ from a set of homogeneous, agriculture-oriented, and scattered villages into a complex system of functionnally diverse, competing, and hierarchised urban settlements. In this paper we show how several modifications of rules and parameters alter further the spatial and hierarchical structure of the simulated urban system.

Intelligent Adaptive Information Agents

Abstract: Adaptation in open, multi-agent information gathering systems is important for several reasons. These reasons include the inability to accurately predict future problem-solving workloads, future changes in existing information requests, future failures and additions of agents and data supply resources, and other future task environment characteristic changes that require system reorganization. We have developed a multi-agent distributed system infrastructure, RETSINA (REusable Task Structure-based Intelligent Network Agents) that handles adaptation in an open Internet environment. Adaptation occurs both at the individual agent level as well as at the overall agent organization level. The RETSINA system has three types of agents. Interface agents interact with the user receiving user specifications and delivering results. They acquire, model, and utilize user preferences to guide system coordination in support of the user‘s tasks. Task agents help users perform tasks by formulating problem solving plans and carrying out these plans through querying and exchanging information with other software agents. Information agents provide intelligent access to a heterogeneous collection of information sources. In this paper, we concentrate on the adaptive architecture of the information agents. We use as the domain of application WARREN, a multi-agent financial portfolio management system that we have implemented within the RETSINA framework.

Using multi-agent architecture in FMS for dynamic scheduling

Abstract: The proposed scheduling strategy is based on a multi-agent architecture. Each agent of this architecture is dedicated to a work centre (i.e. a set of resources of the manufacturing system); it selects locally and dynamically the most suitable dispatching rules. Depending on local and global considerations, a new selection is carried out each time a predefined event occurs (for example, a machine becomes available, or a machine breaks down). The selection depends on: (1) primary and secondary performance objectives, (2) the operating conditions, and (3) an analysis of the system state, which aims to detect particular symptoms from the values of certain system variables. We explain how the scheduling strategy is shared out between agents, how each agent performs a local dynamic scheduling by selecting an adequate dispatching rule, and how agents can coordinate their actions to perform a global dynamic scheduling of the manufacturing system. Each agent can be implemented through object-oriented formalisms. The selection method is improved through the optimization of the numerical thresholds used in the detection of symptoms. This approach is compared with the use of SPT, SIX, MOD, CEXSPT and CR/SPT on a jobshop problem, already used in other research works. The results indicate significant improvements.

Modelling and Design of Multi-Agent Systems

Abstract: Agent technologies are now being applied to the development of large-scale commercial and industrial software systems. Such systems are complex, involving hundreds, perhaps thousands of agents, and there is a pressing need for system modelling techniques that permit their complexity to be effectively managed, and principled methodologies to guide the process of system design. Without adequate techniques to support the design process, such systems will not be sufficiently reliable, maintainable or extensible, will be difficult to comprehend, and their elements will not be re-usable.

Issues in multiagent design systems

Abstract: Knowledge based design integrates a broad range of highly specialized knowledge from expert sources to synthesize or refine a design. Knowledge-based design systems automate at least some of these knowledge sources. However, the constant evolution of standards, technologies, and a dynamic marketplace demands a high degree of adaptability in both design expertise and in the process of applying that expertise. The need for diverse, highly sophisticated, and rapidly changing skills and knowledge makes the multiagent paradigm particularly appropriate for knowledge-based design. As researchers apply multiagent technologies to design domains, challenges include supporting interoperability among heterogeneous agents on diverse platforms, coordinating the design process, and managing conflict. This article surveys the state of the art in multiagent systems, through examples of projects and techniques, and then presents several questions that elicit the requirements and goals of a proposed multiagent design application.

On the Formal Specification and Verification of Multi-Agent Systems

Abstract: This article describes first steps towards the formal specification and verification of multi-agent systems, through the use of temporal belief logics. The article first describes Concurrent METATEM, a multi-agent programming language, and then develops a logic that may be used to reason about Concurrent METATEM systems. The utility of this logic for specifying and verifying Concurrent METATEM systems is demonstrated through a number of examples. The article concludes with a brief discussion on the wider implications of the work, and in particular on the use of similar logics for reasoning about multi-agent systems in general.

Cooperative information-gathering: a distributed problem-solving approach

Abstract: Two approaches to the problem of information-gathering, that may be characterised as distributed processing and distributed problem-solving, are contrasted. The former is characteristic of most existing information-gathering systems, and the latter is central to research in multi-agent systems. The features of complex information-carrying environments and the information-gathering task are examined, demonstrating both the utility of viewing information-gathering as distributed problem-solving and difficulties with viewing it as distributed processing. A new approach is proposed to information-gathering based on the distributed problem-solving paradigm and its attendant body of research in multi-agent systems and distributed artificial intelligence. This approach, called cooperative information-gathering, involves concurrent, asynchronous discovery and composition of information spread across a network of information servers. Top-level queries drive the creation of partially elaborated information-gathering plans, resulting in the employment of multiple semi-autonomous cooperative agents for the purpose of achieving goals and subgoals within those plans. The system as a whole satisfies, trading off solution quality and search cost while respecting user-imposed deadlines. Current work on distributed and agent-based approaches to information-gathering is also surveyed.

Engineering Intelligent Hybrid Multi-Agent Systems

Abstract: Preface. 1. Why Intelligent Hybrid Systems. 2. Methodologies. 3. Intelligent Fusion and Transformation Systems. 4. Intelligent Combination Systems. 5. Knowledge Discovery, Data Mining and Hybrid Systems. 6. Association Systems - Task Structure Level Associative Hybrid Architecture. 7. Intelligent Multi-Agent Hybrid Computational Architecture - Part I. 8. Intelligent Multi-Agent Hybrid Computational Architecture - Part II. 9. Alarm Processing - An Application of IMAHDA. 10. Agent Oriented Analysis and Design of the RTAPS - Part I. 11. Agent Oriented Analysis and Design of the RTAPS - Part II. 12. RTAPS Implementation. 13. From Data Repositories to Knowledge Repositories. 14. IMAHDA Revisited. Appendices: A. Input Features of the Animal Domain. B. Classes in the Animal Domain. C. TTS Power Network. D. TTS Substation Power Network. E. Real Time Alarm Data. Index.

Multi-Agent-Systems Based on Coloured Petri Nets

Abstract: Based on Y. Shoham's paradigm, called Agent-Oriented Programming (AOP), multi-agent-systems are presented as a specialization of distributed, Object-Oriented systems. Equipped with knowledge, general concurrent inference mechanisms dealing with this knowledge, and a declarative agent program, these multi-agent-systems are intended to be a foundation of a new approach uniting advantages of many contributing areas: The precise semantics of Petri nets, the abstraction and encapsulation proposed in Object-Oriented approaches, and the power of logic programming, making it easy to adopt well-known AI-methods. As an example, an urban traffic information system will be designed which solves path searching problems in a distributed graph.

A distributed decision support system for strategic planning

Abstract: Recent advances in artificial intelligence, particularly in the field of multi-agent theory, offer great promises in modeling strategic planning processes. In this domain, the ability to introduce distinct cognitive agents which cooperate to solve the problem enables the processing of more complex and ill-structured problems. This paper presents a general framework for building a distributed strategic decision support system (DSDSS) which integrates both advances in distributed decision making and distributed artificial intelligence. It goes on to describe a cooperative and distributed system with two specific features: the users intervene as human agents in the solution formation, and strategic knowledge and domain knowledge are distributed in different agents which communicate through various blackboards and message passing. An example is provided in the field of strategic marketing which illustrates how the system operates.

Intelligent agents in the nuclear industry

Abstract: Looks at how cooperative multiagent systems designed for monitoring and diagnosing real-time nuclear power plant failures can help operators better anticipate operational problems.

Programmable Coordination Media

Abstract: The design, development and maintenance of multi-component software systems often suffer from the lack of suitable coordination abstractions. The aim of this paper is to show the benefits of coordination models based on global communication abstractions whose behaviour is not fixed, but is extensible so as to accomplish the intended behaviour of the whole system. Accordingly, we propose the notion of programmable coordination medium as an abstraction provided by the coordination model around which the global behaviour of a coordination architecture can be designed. As an example, we show how a Linda-based approach can be empowered by exploiting the notion of programmable tuple space, as supported by the ACLT coordination model.

Formalisms for multi-agent systems

Abstract: As computer scientists, our goals are motivated by the desire to improve computer systems in some way: making them easier to design and implement, more robust and less prone to error, easier to use, faster, cheaper, and so on. In the field of multi-agent systems, our goal is to build systems capable of flexible autonomous decision making, with societies of such systems cooperating with one-another. There is a lot of formal theory in the area but it is often not obvious what such theories should represent and what role the theory is intended to play. Theories of agents are often abstract and obtuse and not related to concrete computational models.

Towards agent systems engineering

Abstract: The term “ agent ” has became a buzzword these days, not only in academic circles, but also in some computer magazines and application fields of computer science like manufacturing and logistics. Hence, there is a pressing need for a design methodology for multi-agent systems. Or even stronger, there is a demand for an agent engineering technology, which includes computer assistance during the design phases, for the validation of the designed system, and for the implementation of the multi-agent system as a physically distributed system. This status report will introduce the field of multi-agent systems and its design. Three prominent applications will serve as a first motivation of the theme. Based on the ideas of the agent examples a discussion on the term agent will serve as a first motivation of the theme. Based of the theme. Based on the ideas of the agent architecture of an agent, its communication capabilities, and planning in a multi-agent context. After this broad technical introduction the main topic of this work will be tackled. An introduction to five methodologies for the design of multi-agent systems will be given and a new one, the AWIC method, will be presented. Eventually a brief discussion about the multi-agent design approaches will be given, the missing correlations to the task definitions will be critizised, and further research directions will be proposed.

Commitments Among Autonomous Agents in Information-Rich Environments

Abstract: Commitments are crucial to understanding and designing autonomous agents and multiagent systems. We propose a definition of commitments that applies especially well to agents in information-rich applications, such as electronic commerce and virtual enterprises. Our approach has a number of important features, including not gratuitously translating social concepts to psychological concepts distinguishing between satisfied and inapplicable commitments incorporating social policies to handle the creation, satisfaction, and cancelation of commitments relating commitments to organizational structure in a multiagent system showing how commitments are acquired by agents as a consequence of adopting a role.

PECS: A Reference Model for the Simulation of Multi-Agent Systems

Abstract: There is currently a multitude of design approaches all concerned with building simulation models for multi-agent systems. The majority of the designs, however, focus on the requirements of specific application domains. We suggest that it would be desirable to develop a modelling methodology which can act as a generic platform from which to construct simulation models for multi-agent systems. In order to promote standardisation of modelling methodology, this paper presents a first-cut reference model whose feasibility will subsequently be demonstrated by a number of applications.