A general game player is an agent capable of taking as input a description of a game’s rules in a formal language and proceeding to play without any subsequent human input. To do...
Reinforcement learning has been used for training game playing agents. The value function for a complex game must be approximated with a continuous function because the number of ...
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
In order to understand whether conceptual obscurity is truly the reason for the slow uptake of IMS Learning Design (LD), we have initiated an investigation into teachers' unde...
Michael Derntl, Susanne Neumann, Dai Griffiths, Pe...
This paper introduces a novel method for real-time estimation of slowly varying parameters in nonlinear dynamical systems. The core concept is built upon the principles of symboli...