Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
This paper presents a model of autonomy called autonomy with regard to an attribute applicable to cognitive and not cognitive artificial agents. Three criteria (global / partial, ...
We present a universal mechanism that can be combined with existing trust models to extend their capabilities towards efficient modelling of the situational (contextdependent) tr...
The need for rapid and cost-effective development Intelligent Tutoring Systems with flexible pedagogical approaches has led to a demand for authoring tools. The authoring systems ...
Agents that operate in a multi-agent system can benefit significantly from adapting to other agents while interacting with them. This work presents a general architecture for a ...