{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/project-proposal-a-modular-reinforcement","title":"Project proposal: A modular reinforcement learning based automated theorem prover","arxiv_id":"2209.02562","date":"2022-09-06","proceeding":null,"authors":["Boris Shminke"],"abstract":"We propose to build a reinforcement learning prover of independent components: a deductive system (an environment), the proof state representation (how an agent sees the environment), and an agent training algorithm. To that purpose, we contribute an additional Vampire-based environment to $\\texttt{gym-saturation}$ package of OpenAI Gym environments for saturation provers. We demonstrate a prototype of using $\\texttt{gym-saturation}$ together with a popular reinforcement learning framework (Ray $\\texttt{RLlib}$). Finally, we discuss our plans for completing this work in progress to a competitive automated theorem prover.","url_abs":"https://arxiv.org/abs/2209.02562v1","url_pdf":"https://arxiv.org/pdf/2209.02562v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"project-proposal-a-modular-reinforcement","repo_url":"https://github.com/inpefess/basic-rl-prover","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"openai-gym","task_name":"OpenAI Gym"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"},{"task_slug":"rllib","task_name":"rllib"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}