Multi-Agent Cooperation for Particle Accelerator Control

We present practical investigations in a real industrial controls environment for justifying theoretical DAI (Distributed Artificial Intelligence) results, and we discuss theoretical aspects of practical investigations for accelerator control and operation. A generalized hypothesis is introduced, based on a unified view of control, monitoring, diagnosis, maintenance and repair tasks leading to a general method of cooperation for expert systems by exchanging hypotheses. This has been tested for task and result sharing cooperation scenarios. Generalized hypotheses also allow us to treat the repetitive diagnosis-recovery cycle as task sharing cooperation. Problems with such a loop or even recursive calls between the different agents are discussed

Cooperation in Industrial Systems

ARCHON is an ongoing ESPRIT II project (P-2256) which is approximately half way through its five year duration. It is concerned with defining and applying techniques from the area of Distributed Artificial Intelligence to the development of real-size industrial applications. Such techniques enable multiple problem solvers (e.g. expert systems, databases and conventional numerical software systems) to communicate and cooperate with each other to improve both their individual problem solving behavior and the behavior of the community as a whole. This paper outlines the niche of ARCHON in the Distributed AI world and provides an overview of the philosophy and architecture of our approach the essence of which is to be both general (applicable to the domain of industrial process control) and powerful enough to handle real-world problems

Aspects of cooperating agents

An overview on aspects about cooperating agents is presented. As multiagent systems are various, we start with a classification of multiagent systems which is particularly influenced by an article from Decker, Durfee, and Lesser [Decker& 89]. In the following, the aspects of communication, planning, and negotiation are examined. On the occasion of communication, the discussion is split into: no communication - simple protocols - artificial languages. The planning aspect is broken into sections: from classical to multiagent planning - a general multiagent planning theory - intention - intention-directed multiagent planning. Finally, a summary of Brigitte and Hassan Lâasri and Victor Lesser\u27s negotiation theory will be presented

A knowledge representation model to support concurrent engineering team working

This thesis demonstrates that a knowledge representation model can provide considerable support to concurrent engineering teams, by providing a sound basis for creation of necessary software applications. This is achieved by demonstrating that use of the knowledge representation model facilitates the capture, interpretation and implementation of important aspects of the multiple, diverse types of expertise which are essential to the successful working of concurrent engineering project teams. The varieties of expertise which can be modelled as instances of the knowledge representation model range from specialist applications, which support particular aspects of design, by assisting human designers with highly focused skills and knowledge sets, to applications which specialise in management or coordination of team activities. It is shown that both these types of expertise are essential for effective working of a concurrent engineering team. Examination of the requirements of concurrent engineering team working indicate that no single artificial intelligence paradigm can provide a satisfactory basis for the whole range of possible solutions which may be provided by intelligent software applications. Hence techniques, architectures and environments to support design and development of hybrid software expertise are required, and the knowledge representation model introduced in this research is such an architecture. The versatility of the knowledge representation model is demonstrated through the design and implementation of a variety of software applications

A multi-agent environment in robotics

The use of Multi-Agent Systems as a Distributed AI paradigm for Robotics is the principal aim of our present work. In this paper we consider the needed concepts and a suitable architecture for a set of Agents in order to make it possible for them to cooperate in solving non-trivial tasks. Agents are sets of different software modules, each one implementing a function required for cooperation. A Monitor, an Acquaintance and Self-knowledge Modules, an Agenda and an Input queue, on the top of each Intelligent System, are fundamental modules that guarantee the process of cooperation, while the overall aim is devoted to the community of cooperative Agents. These Agents, which our testbed concerns, include Vision, Planner, World Model and the Robot itself.info:eu-repo/semantics/publishedVersio

Main topics of DAI : a review

A new branch of artificial intelligence, distributed AI, has developed in the last years. Topic is the cooperation of AI-systems which are distributed among different autonomous agents. The thereby occuring problems extend the traditional AI spectrum and are presented along the major DAI-relevant topics: Knowledge representation, task-decomposition and -allocation, interaction and communication, cooperation, coordination and coherence, organizational models, agent\u27s modelling of other agents and conflict resolution strategies (e.g. negotiation). First we try to describe the role of DAI within AI. Then every subsection will take up one special aspect, illuminate the occurring problems and give links to solutions proposed in literature. Interlaced into this structure are sketchy descriptions of a few very prominent and influential DAI systems. In particular we present the Contract Net Protocol, the Distributed Vehicle Monitoring Testbed, the Air Traffic Control problem and the Blackboard Architecture