International Journal of Cooperative Information Systems

This paper describes work undertaken in the ADEPT (Advanced Decision Environment for Process Tasks) project towards developing an agent-based infrastructure for managing business processes. We describe how the key technology of negotiating, service providing, autonomous agents was realized and demonstrate how this was applied to the BT (British Telecom) business process of providing a customer quote for network services.

Real world engineering design projects require the cooperation of multidisciplinary design teams using sophisticated and powerful engineering tools. The individuals or the individual groups of the multidisciplinary design teams work in parallel and independently often for quite a long time with different tools located on various sites. In order to ensure the coordination of design activities in the different groups or the cooperation among the different tools, it is necessary to develop an efficient design environment. This paper discusses a distributed architecture for integrating such engineering tools in an open design environment, organized as a population of asynchronous cognitive agents. Before introducing the general architecture and the communication protocol, issues about an agent architecture and inter-agent communications are discussed. A prototype of such an environment with seven independent agents located in several workstations and microcomputers is then presented and demonstrated on an example of a small mechanical design.

The centralized planning and control that has defined the traditional information processing structure of manufacturing systems is no longer suited to the current rapidly changing manufacturing environment. For efficient use of manufacturing resources and increased flexibility, it is necessary to migrate to a distributed information processing system in which individual entities can work cooperatively towards overall system goals. The next generation of manufacturing systems requires such an information technology framework to integrate the system components and activities into a larger collaborative enterprise. This paper describes a multi-agent approach to concurrent design, manufacturability analysis, process planning, routing and scheduling. A heterogeneous multi-agent concurrent engineering system consisting of multiple feature-based design sub-systems, multiple simulated shop-floor resource groups, a supervisory control interface and the coordination mechanisms for multi-agent cooperation, has been developed. The architecture of this distributed system and the associated implementation issues are discussed.

We are investigating techniques for developing distributed and adaptive collections of information agents that coordinate to retrieve, filter and fuse information relevant to the user, task and situation, as well as anticipate user's information needs. In our system of agents, information gathering is seamlessly integrated with decision support. The task for which particular information is requested of the agents does not remain in the user's head but it is explicitly represented and supported through agent collaboration. In this paper we present the distributed system architecture, agent collaboration interactions, and a reusable set of software components for structuring agents. The system architecture 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. We have implemented this system framework and are developing collaborating agents in diverse complex real world tasks, such as organizational decision making, investment counseling, health care and electronic commerce.

Exploration is a central issue for autonomous agents which must carry out navigation tasks in environments of which a description is not known a priori. In our approach the environment is described, from a symbolic point of view, by means of a graph; clustering techniques allow for further levels of abstraction to be defined, leading to a multi-layered representation. In this work we propose an unsupervised exploration algorithm in which several agents cooperate to acquire knowledge of the environment at the different abstraction levels. All agents are equal and pursue the same local exploration strategy; nevertheless, the existence of multiple levels of abstraction in the environment representation allows for the agents' behavior to differ. Agents carry out exploration at different abstraction levels, aimed at reproducing an ideal exploration profile; each agent dynamically selects its exploration level, based on the current demand. Inter-agent communication allows for the agents to share their knowledge and to record acquaintances of the other agents. A communication protocol for organizing teams of agents is provided.

As agents see more use in dynamic, distributed information networks, information sharing facilitators, such as the SHADE matchmaker, and underlying knowledge-based agent communication protocols, such as the Knowledge Query and Manipulation Language, will see increased use. We have created several communities of agents collaborating via KQML and matchmaking within the domains of collaborative engineering and satellite image retrieval. Based on these experiences, matchmaking has proven to be very beneficial for multi-agent systems, but we have also identified a number of issues and extensions that are not only vital to KQML-based matchmaking, but to inter-agent protocols in general. These include representational approaches to advertising complex databases, approaches to error recovery and response timing, maintaining consistency among information providers, scalability, security, persistent requests in information brokering, and the dilemma between explicit vs implicit brokering.

The agent view provides a level of abstraction at which we envisage computational systems carrying out cooperative work by interoperating globally across networks connecting people, organizations and machines. A major challenge in building such systems is coordinating the behavior of the individual agents to achieve the individual and shared goals of the participants. As part of a larger project targeted at developing an Agent Building Shell for multiagent applications, we have designed and implemented a coordination language aimed at explicitly representing, applying and capturing coordination knowledge for multiagent systems. The language provides KQML-based communication, an agent definition and execution environment, support for modeling interactions as multiple structured conversations among agents, rule-based approaches to conversation selection and execution, as well as an interactive tool for in context acquisition and debugging of cooperation knowledge. The paper presents these components in detail and then shows how the coordination language is used in the Agent Building Shell to manage content-based information distribution scenarios among agents and the coordination aspects of conflict management processes that occur when agents encounter inconsistencies. The major application of the system is the construction and integration of multiagent supply chain systems for manufacturing enterprises. This application is used throughout the paper to illustrate the introduced concepts and language constructs.

We present a theory and a tool for the treatment of problems arising when a decision making agent faces a situation involving a choice between a finite set of strategies, having access to a finite set of autonomous agents reporting their opinions. Each of these agents may itself be a decision making agent, and the theory is independent of whether there is a specific coordinating agent or not. Any decision making agent is allowed to assign different credibilities to the statements made by the other autonomous agents. The theory admits the representation of vague and numerically imprecise information, and the evaluation results in a set of admissible strategies by using criteria conforming to classical statistical decision theory. The admissible strategies can be further investigated with respect to strength and also with respect to the range of values that makes them admissible.

Two or more companies, each with its own knowledge base, may merge. In that case one option is to merge the knowledge bases into one knowledge base. It can happen that some of the information contained in one or more knowledge bases may be in conflict with information in the other knowledge bases. There may be several such points of conflict and any information may be involved in several different such points of conflict. In that case, the integrator of the knowledge bases may prefer a certain claim to another in one conflict-point without necessarily preferring that claim in another conflict-point.

Our work constructs a framework within which the consequences of a set of such preferences (expressed as priorities among sets of statements) can be computed. We give three types of semantics for priorities, two of which are shown to be equivalent to one another. The third type of semantics for priorities is shown to be more cautious than the other two. In terms of these semantics for priorities, we give a function for combining knowledge from different sources such that the combined knowledge is conflict-free and satisfies all the priorities.