Learning by observation allows a software agent to learn by watching an expert perform a task. This transfers the burden of training from the expert, who would traditionally need to program the agent, to the agent itself. Most existing approaches to learning by observation perform their observation in a purely passive manner. We propose a case-based reasoning agent that is able to observe passi...

Mobile agents can migrate among nodes to perform a set of management tasks at each of the visited nodes. Existing mobile agent-based network management systems often assume that their mobile agents are designed to work in particular networks to raise the efficiency of agent migration among multiple nodes. Unfortunately, such mobile agents cannot be reused in different networks. This paper propo...

Different agents in a multiagent system might have different solution quality or preference criteria. Therefore, when solving problems collaboratively using CBR, case reuse must take this into account. In this paper we propose ABARC, a model for multiagent case reuse, which divides case reuse in two stages: individual reuse, where agents generate full solutions internally, and multiagent reuse,...

agent oriented software engineering (aose) is an emerging field in computer science  and  proposes some systematic ideas for multi agent systems analysis, implementation and maintenance. despite the various methodologies introduced in the agent-oriented software engineering, the main challenges are defects in different aspects of methodologies. according to the defects resulted from weaknesses ...

Recent events have highlighted the importance of good models of crowds, however many existing crowd models are either computationally inefficient, or are missing a crucial human behaviour in crowds: local pushing. After discussing some essential aspects of force in crowds, and considering some existing models, we propose an efficient agent-based model of crowd evacuation that incorporates pushi...

This article presents the first attempt to construct a computational model of common ground. Four corpus-based metrics are presented that estimate what facts are likely to be in common ground. The proposed metrics were evaluated in an experiment with human participants, focussing on a domain of famous people. The results are encouraging: two of the proposed metrics achieved a large positive cor...

Providing seamless, fluid interaction between team members, contractors, consultants from any world-wide location stimulates virtual organisations. The agent-based team work environment UNITE offers team members intuitive and ubiquitous access to each other, and to information and resources of their project, secure and transparent to their physical workplaces and their own tools. Thus, team foc...

We suggest that, as an extension to traditional historical analysis, it is potentially insightful and useful to model guerrilla wars in agent-based terms. Accordingly, the Iruba agent-based model of a guerrilla war has been designed and implemented. Some experimental results obtained with the model and conclusions that may be drawn from them are reported, particularly in relation to Guevara and...

Agent-Based Modeling has the capability to become a very powerful tool in economics, but in order to achieve this will require a great deal of effort on the part of its current practitioners. Economics at its core studies people and their actions. This is inherently difficult to do since the motivation of people is not always discernible. A method by which the variety of human behavior could be...

This paper presents an integrative agent model for adaptive human-aware information presentation. Within the agent model, meant to support humans in demanding tasks, a domain model is integrated which consists of a dynamical model for human functioning, and a model determining the effects of information presentation. The integrative agent model applies modelbased reasoning methods to the domain...