— Hybrid deliberative-reactive control architectures are a popular and effective approach to the control of robotic navigation applications. However, the design of said architect...
Abstract. The growing availability of measurement devices in the operating room enables the collection of a huge amount of data about the state of the patient and the doctors’ pr...
Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
An agent's beliefs usually depend on cognitive factors, but also affective factors may play a role. This paper presents an agent model that shows how such affective effects on...
This paper investigates the use of reinforcement learning in electric power system emergency control. The approach consists of using numerical simulations together with on-policy M...