We present our work on using statistical, corpus-based machine learning techniques to simultaneously recognize an agent's current goal schemas at various levels of a hierarch...
In this work, we extend the architecture of agents (and robots) based upon fixed, one-size-fits-all cycles of operation, by providing a framework of declarative specification of ag...
Antonis C. Kakas, Paolo Mancarella, Fariba Sadri, ...
Multiagent Systems are potential computational systems for various practical applications, tools, and so on. Multiagent simulation is one of the remarkable application to evaluate ...
Aperiodic dynamics are known to be essential in the formation of perceptual mechanisms and representations in biological organisms. Advances in neuroscience and computational neur...
The social laws paradigm represents an important approach to the co-ordination of behaviour in multi-agent systems. In this paper we examine the relationship between social laws an...