LeDeepChef: Deep Reinforcement Learning Agent for Families of Text-Based Games

Understand

While Reinforcement Learning (RL) approaches lead to significant achievements in a variety of areas in recent history, natural language tasks remained mostly unaffected, due to the compositional and combinatorial nature that makes them notoriously hard to optimize.

• With the emerging field of Text-Based Games (TBGs), researchers try to bridge this gap.
• Inspired by the success of RL algorithms on Atari games, the idea is to develop new methods in a restricted game world and then gradually move to more complex environments.
• Previous work in the area of TBGs has mainly focused on solving individual games.