In this paper we present ISLANDER, a tool for the specification and verification of agent mediated electronic institutions. We have defined a textual declarative language for the specification of the components of an institution. Also an IS-LANDER editor is presented. It facilitates the work of the institution designer permitting the combination of graphical and textual specifications. We take the stance that a verifiable formal specification is needed before starting the development of complex systems. This tool is our first step towards having a framework for the design and development of infrastructures for open multi-agent systems. Categories and Subject Descriptors

Scientific research and practice in multiagent systems focuses on constructing computational frameworks, principles, and models for how both small and large societies of intelligent, semiautonomous agents can interact effectively to achieve their goals. This article provides a personal view of the key application areas for cooperative multiagent systems, the major intellectual problems in building such systems, the underlying principles governing their design, and the major directions and challenges for future developments in this field. Index Terms---Multiagent systems, coordination, cooperation, distributed problem solving, distributed artificial intelligence, computational organizations. ------------------------------ ###p### ------------------------------ 1INTRODUCTION ULTIAGENT systems are computational systems in which two or more agents interact or work together to perform some set of tasks or to satisfy some set of goals. These systems may be comprised of homogeneous o...

This paper shows how to use a decision-theoretic task scheduler in order to automatically generate efficient intention selection functions for BDI agent-oriented programming languages. We concentrate here on the particular extensions to a known BDI language called AgentSpeak(L) and its interpreter which were necessary so that the integration with a task scheduler was possible. The proposed language, called AgentSpeak(XL), has several other features which increase its usability; some of these are indicated briefly in this paper. We assess the extended language and its interpreter by means of a factory plant scenario where there is one mobile robot that is in charge of packing and storing items, besides other administrative and security tasks. This case study and its simulation results show that, in comparison to AgentSpeak(L), AgentSpeak(XL) provides much easier and efficient implementation of applications that require quantitative reasoning, or require specific control over intentions (e.g., for giving priority to certain tasks once they become intended).

The World Wide Web has become an invaluable information resource but the explosion of available information has made web search a time consuming and complex process. The large number of information sources and their different levels of accessibility, reliability and associated costs present a complex information gathering control problem. This paper describes the rationale, architecture, and implementation of a next generation information gathering system – a system that integrates several areas of Artificial Intelligence research under a single umbrella. Our solution to the information explosion is an information gathering agent, BIG, that plans to gather information to support a decision process, reasons about the resource trade-offs of different possible gathering approaches, extracts information from both unstructured and structured documents, and uses the extracted information to refine its search and processing activities.

Abstract. To scale agent technologies for widespread use in open systems, agents must have an understanding of the organizational context in which they operate. In this paper we focus on the issue of task valuation and action selection in socially situated or organized agents – specifically on the issue of quantifying agent relationships and relating work motivated by different sources. 1

We investigate the concept of artificial societies and identify a number of separate classes of such societies. These are compared in terms of openness, flexibility, stability, and trustfulness. The two most obvious types of artificial societies are the open societies, where there are no restrictions for joining the society, and the closed societies, where it is impossible for an "external agent" to join the society. We argue that whereas open societies supports openness and flexibility, closed societies support stability and trustfulness.

The idea of ubiquitous computing and smart environments is no longer a dream and has long become a serious area of research and soon this technology will start entering our every day lives. There are two major obstacles that prevent this technology from spreading. First, di#erent smart spaces are equipped with very di#erent kinds of devices (e.g. a projector vs. a computer monitor, vs. a TV set). Second, multiple applications running in a space at the same time inevitably contend for those devices and other scarce resources. The underlying software in a smart space needs to provide tools for self-adaptivity in that it shields the rest of the software from the physical constraints of the space, and that it dynamically adjusts the allocation of scarce resources as the number and priorities of active tasks change.

Intelligent environments are an interesting development and research application problem for multiagent systems. The functional and spatial distribution of tasks naturally lends itself to a multi-agent model and the existence of shared resources creates interactions over which the agents must coordinate. In the UMASS Intelligent Home project we have designed and implemented a set of distributed autonomous home control agents and deployed them in a simulated home environment. Our focus is primarily on resource coordination, though this project has multiple goals and areas of exploration ranging from the intellectual evaluation of the application as a general MAS testbed to the practical evaluation of our agent building and simulation tools. 1 Introduction The intelligent home project (IHome) at the UMASS multi-agent systems lab is an exploration in the application of multi-agent systems technology to the problem of managing an intelligent environment. We have implemented a sophisticate...

This paper presents and evaluates a decision making framework that enables autonomous agents to dynamically select the mechanism they employ in order to coordinate their inter-related activities. Adopting this framework means coordination mechanisms move from the realm of something that is imposed upon the system at design time, to something that the agents select at run-time in order to fit their prevailing circumstances and their current coordination needs. Using this framework, agents make informed choices about when and how to coordinate and when to respond to requests for coordination. The framework is empirically evaluated, in a grid world scenario, and we highlight those types of environments in which it is e#ective.

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