An Incremental Process for the Development of Multi-agent Systems in Event-B

A multi-agent system is a group of software or hardware agents that cooperate or compete to achieve individual or shared goals. A method for developing a multi-agent system must be capable of modelling the concepts that are central to multi-agent systems. These concepts are identified in a review of Agent Oriented Software Engineering methodologies. The rigorous development of complex systems using formal methods can reduce the number of design faults. Event-B is a formal method for modelling and reasoning about reactive and distributed systems. There is currently no method that guides the developer specifically in the modelling of agent-based concepts in Event-B. The use of formal methods is seen by some developers as inaccessible. This thesis presents an Incremental Development Process for the development of multi-agent systems in Event-B. Development following the Incremental Development Process begins with the construction of informal models, based on agent concepts. The informal models relate system goals using a set of relationships. The developer is provided with guidance to construct formal Event-B models based on the informal design. The concepts that are central to multi-agent systems are captured in the Event-B models through the translation from the goal models. The Event-B models are refined and decomposed into specifications of roles that will be performed by the agents of the system. Two case studies illustrate how the Incremental Development Process can be applied to multi-agent systems. An additional aid to the developer presented in this thesis is a set of modelling patterns that provide fault-tolerance for Event-B models of interacting agents

A group learning management method for intelligent tutoring systems

In this paper we propose a group management specification and execution method that seeks a compromise between simple course design and complex adaptive group interaction. This is achieved through an authoring method that proposes predefined scenarios to the author. These scenarios already include complex learning interaction protocols in which student and group models use and update are automatically included. The method adopts ontologies to represent domain and student models, and object Petri nets to specify the group interaction protocols. During execution, the method is supported by a multi-agent architecture

KEMNAD: A Knowledge Engineering Methodology for Negotiating Agent Development

Automated negotiation is widely applied in various domains. However, the development of such systems is a complex knowledge and software engineering task. So, a methodology there will be helpful. Unfortunately, none of existing methodologies can offer sufficient, detailed support for such system development. To remove this limitation, this paper develops a new methodology made up of: (1) a generic framework (architectural pattern) for the main task, and (2) a library of modular and reusable design pattern (templates) of subtasks. Thus, it is much easier to build a negotiating agent by assembling these standardised components rather than reinventing the wheel each time. Moreover, since these patterns are identified from a wide variety of existing negotiating agents(especially high impact ones), they can also improve the quality of the final systems developed. In addition, our methodology reveals what types of domain knowledge need to be input into the negotiating agents. This in turn provides a basis for developing techniques to acquire the domain knowledge from human users. This is important because negotiation agents act faithfully on the behalf of their human users and thus the relevant domain knowledge must be acquired from the human users. Finally, our methodology is validated with one high impact system