December 03, 2019 preprint Open access Leveraging Procedural Generation to Benchmark Reinforcement Learning arXiv (Cornell University) DOI: 10.48550/arxiv.1912.01588 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 8 stored of 163 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access AMaze: an intuitive benchmark generator for fast prototyping of generalizable agents 2025 Frontiers in Artificial Intelligence article Computer Science Reinforcement Learning in Robotics Open access 1 citations Chatter Generation through Language Models 2023 IEEE Conference on Games (CoG) conference-paper Computer Science Speech and dialogue systems 8 citations Learning General Policies with Policy Gradient Methods 2023 conference-paper Computer Science Reinforcement Learning in Robotics Open access 10 citations Towards verifiable Benchmarks for Reinforcement Learning 2022 IEEE Conference on Games (CoG) conference-paper Computer Science Reinforcement Learning in Robotics 3 citations Two-Agent Self-Play 2022 Springer eBooks book-chapter Computer Science Reinforcement Learning in Robotics 0 citations Further Developments 2022 Springer eBooks book-chapter 0 citations Procedural Content Generation: Better Benchmarks for Transfer Reinforcement Learning 2021 IEEE Conference on Games (CoG) conference-paper Computer Science Reinforcement Learning in Robotics Open access 11 citations Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning 2020 IEEE Conference on Games (CoG) conference-paper Computer Science Reinforcement Learning in Robotics Open access 3 citations 8 results References 0