Edward Grefenstette: Teaching Artificial Agents to Understand Language by Modelling Reward

Recent progress in Deep Reinforcement Learning has shown that agents can be taught complex behaviour and solve difficult tasks, such as playing video games from pixel observations, or mastering the game of Go without observing human games, with relatively little prior information. Building on these successes, researchers such as Hermann and colleagues have sought to apply these methods to teachin simulationagents to complete a variety of tasks specified by combinatorially rich instruction languages. In th