Nowadays multi-agent applications are more and more openness. That brings the risk to deal with to autonomous agents i.e. agents not respecting the society rules. To insure a coherent behaviour the application require tools to control and regulate the system overall functioning. Moreover they should provide the system with mechanisms to enforce global laws on the autonomous agents operating in ...

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 realised and demonstrate how this was applied to the BT (British Telecom) business process of providing a customer ...

In the virtual game world prototype World of Minds that uses the Mind Module, a semi-autonomous agent architecture, the notion of sentiments, or emotional attachments between objects, is what constitutes the deep structure in the game world. In this paper a play test is presented where sentiments are instantiated in three different ways; randomly, by choice of the player and through interaction...

Norms have been considered an attractive means for the regulation of the dynamics of multi systems (MAS). Typically, it is left for the individual agents to apply (general) norms to the particular concrete situations that arise during the operation of the system. This paper summarises our work on situated normative infrastructures for multi-agent systems, which aim to facilitate the operational...

For an autonomous agent, performing a task in a spatio-temporal environment often requires interaction with other agents. Such interaction can be initiated by ad-hoc collaborative planning and decision-making, which then leads to physical support on site. On-site collaboration is important for a variety of operations, such as search-and-rescue or pick-up-and-delivery. Tasks are performed throug...

In order to claim fully general intelligence in an autonomous agent, the ability to learn is one of the most central capabilities. Classical machine learning techniques have had many significant empirical successes, but large real-world problems that are of interest to generally intelligent agents require learning much faster (with much less training experience) than is currently possible. This...

An Autonomous Science Agent is currently flying onboard the Earth Observing One Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and run-time robust execution. Because of the deployment to a remote spacecraft, this Autonomo...

This paper focuses on implementing a multi-agent simulation using distributed Linux cluster for swarm intelligence between multiple agents in the context of a battlefield or hostile area scenario. Different aspects from several different papers can provide ways in which to develop an autonomous agent algorithm. An autonomous agent algorithm will have the group of individual worker agents collec...

Abstract In the near future, autonomous vehicles (AVs) may cohabit with human drivers in mixed traffic. This cohabitation raises serious challenges, both terms of traffic flow and individual mobility, as well from road safety point view. Mixed fail to fulfill expected security requirements due heterogeneity unpredictability drivers, cars could then monopolize Using multi-agent reinforcement lea...