AI Synergies


René Raab

PhD candidate, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)

A Generative Policy Gradient Approach for Learning to Play Text-Based Adventure Games

Text-based adventure games pose a very difficult task for reinforcement learning. Current approaches work well on generated games but are limited to specific (sets of) games only and require knowledge about possible actions in advance. The master’s thesis presented here describes an early first step towards a more generative and general approach of learning to play text-based games by moving from discrete actions to learned continuous action representations.


René Raab graduated from Maastricht University in 2019 receiving an M.Sc. in Artificial Intelligence. He is now a PhD candidate at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) in Germany.


Gamay room
Research presentations AI
Day 3 - Nov 8th

Brewery of Ideas

AI Synergies is organized by VUB/ULB, BNVKI and Brewery of Ideas.

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