In this paper we propose a multiagent architecture for implementing concurrent reinforcement learning, an approach where several agents, sharing the same environment, perceptions ...
In this paper, we present an improved version of the online phase-space learning algorithm of Tsung and Cottrell (1995), called ARTISTE (Autonomous Real-TIme Selection of Training...
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Though attention to evaluating human-robot interfaces has increased in recent years, there are relatively few reports of using evaluation tools during the development of humanrobo...
– This paper presents a hippocampal inspired robot localization model that provides a means for a simple robotic platform with ultrasonic sensors to localize itself. There have b...