Real-time control has become increasingly important as technologies are moved from the lab into real world . . .

Multi-linked negotiation describes a situation where one agent needs to negotiate with multiple agents about different issues, and the negotiation over one issue influences the negotiations over other issues. Multi-linked issues will become important for the next generation of more complicated Multi-Agent Systems. However, most current negotiation research looks only at single issue negotiation and thus does not present techniques to reason and manage multilinked issues. In this paper, we present a technique based on the use of a partial-order schedule and a measure of the schedule, called flexibility, which enables an agent to reason explicitly about the interactions among multiple negotiation issues. We show how an agent uses the partial-order schedule to effectively manage interacting negotiation issues; and how the flexibility is a key measure for ordering and managing negotiation issues. Experimental work is presented which shows this management technique for multilinked negotiation leads to improved performance.

Events fall short to simulate actions of multi-agent systems (MASs). Agents act in dynamic environments, and the characteristics of actions in dynamic environments differ significantly from the properties of events. In this paper, we propose a conceptual model for actions in dynamic environments, based on the concepts influence, activity and effect. The model is especially important for simulating industrial multi-agent systems as it explicitly supports three essential characteristics of actions in dynamic environments: (1) the environment changes while an agent is acting upon it, (2) agents do not control the actual outcome of their actions, and (3) agents do not control the time instant their actions complete. The model enables a developer to incorporate a suitable amount of dynamism with respect to the actions in the simulation in an explicit and systematic way. This allows simulating scenarios where actions do not yield their intended result. We illustrate the model using a scenario in an automated warehouse transportation system and describe the architecture of a prototype that supports the model. 1

This paper addresses the problem of the engineering divergence phenomenon in ABS. This problem is related to the fact that a particular conceptual model may give di#erent outputs according to its implementation. Through two experiments, the paper shows that the implementation of the agents' interaction is one of the factors that are involved in this phenomenon. The underlying idea of this paper is that this problem can be greatly diminished if the analysis of the conceptual model incorporates some key concepts which are crucial for the implementation. To this end, this work proposes to identify two di#erent classes of interaction: weak interactions and strong interactions.

Abstract. Multi-agent systems provide an increasingly popular solution in problem domains that require management of uncertainty and a high degree of adaptability. Robustness is a key design criterion in building multi-agent systems. We present a novel approach for the design of robust multi-agent systems. Our approach constructs a model of the design of a multi-agent system in Alloy, a declarative language based on relations, and checks the properties of the model using the Alloy Analyzer, a fully automatic analysis tool for Alloy models. While several prior techniques exist for checking properties of multi-agent systems, the novelty of our work is that we can check properties of coordination and interaction, as well as properties of complex data structures that the agents may internally be manipulating or even sharing. This is the first application of Alloy to checking properties of multi-agent systems. Such unified analysis has not been possible before. We also introduce the use of a formal method as an integral part of testing and validation. 1

To facilitate the development of multi-agent systems and improve the reusability, robustness and feasibility of these systems, we have developed a role-based agent development framework (RADE). In this paper, we present an integrated approach for modeling, designing and implementing multi-agent systems using RADE. We describe the design of agents and motivations within such framework. We introduce a practical approach for modeling agent’s motivation and specifying agent’s goals, where a role-agent mapping mechanism is developed based on this design. Dynamic task allocation is achieved through the creation of role instances and the mapping from role instances to agents. We also introduce the RTÆMS language based on the extension of TÆMS to model the plan tree for each goal. This representation enables the reuse of general planning/scheduling and collaboration/cooperation mechanisms developed in multi-agent system research community. We have developed an automatic agent generation interface and also implemented a simple demo system in health care domain.

This paper deals with a problem of using multi-agent technology to simulate and resolve the planning problems. Concretely, multi-agent systems (MAS) are used in studying and resolving the optimization problems within the Producer-Customer-Transport (PCT) domain. K e y w o r d s: MAS, supply chain, optimization, simulation 1

Multi-Agent System (MAS) is a suitable programming paradigm for simulating and modeling health care systems and applications, where resources, data, control and services are widely distributed. We have developed a multi-agent software prototype to simulate the activities and roles inside a health care system. The prototype is developed using a framework called Rolebased Agent Development Environment (RADE). In this chapter, we present an integrated approach for modeling, designing and implementing a multi-agent health care simulation system using RADE. We describe the definition of role classes and agent classes, as well as the automatic agent generation process. We illustrate the coordination problem and present a rulebased coordination approach. In the end, we present a runtime scenario of this health care simulation system, which demonstrates that dynamic task allocation can be achieved through the creation of role instances and the mapping from role instances to agents. This scenario also explains how agents coordinate their activities given their local constraints and interdependence among distributed tasks.

Abstract—The development of large-scale distributed multiagent systems in open dynamic environments is a challenge. System behavior is often not predictable and can only be evaluated by execution. This paper proposes a framework to support design and development of such systems: a framework in which both simulation and emulation play an important role. A distributed agent platform (AgentScape) is used to illustrate the potential of the framework. Keywords-multi-agent systems, agent-based simulation, emulation, development, distributed systems I.