Researchers combine reinforcement learning and NLP to escape a Grue monster

AI researchers from Georgia Tech and Microsoft Research created AI that combines reinforcement learning and natural language processing (NLP) to outperform state-of-the-art question-answering AI in eight of nine text adventure games. Researchers say the model MC!Q*BERT is the first known learning agent to consistently get past a bottleneck where a player is eaten by a Grue monster in Zork, one of the first interactive computer games.

MC!Q*BERT is made in part from Q*BERT, a deep reinforcement learning agent that learns and builds a knowledge graph by asking questions about the world. Every observation made throughout the course of a game generates a series of questions that are then converted and added to the knowledge graph.