The deployment of learning resources on the web by different experts has resulted in the accessibility of multiple viewpoints about the same topics. In this work we assume that lea...
In our research we study rational agents which learn how to choose the best conditional, partial plan in any situation. The agent uses an incomplete symbolic inference engine, emp...
Argumentation is a promising approach used by autonomous agents for reasoning about inconsistent/incomplete/uncertain knowledge, based on the construction and the comparison of ar...
So far, most equilibrium concepts in game theory require that the rewards and actions of the other agents are known and/or observed by all agents. However, in real life problems, a...
This paper introduces and describes an innovative modelling approach which utilises models that are synthesised through approximate calculations of user actions and extensive repr...