{"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/learning-light-transport-the-reinforced-way","title":"Learning Light Transport the Reinforced Way","arxiv_id":"1701.07403","date":"2017-01-25","proceeding":null,"authors":["Ken Dahm","Alexander Keller"],"abstract":"We show that the equations of reinforcement learning and light transport\nsimulation are related integral equations. Based on this correspondence, a\nscheme to learn importance while sampling path space is derived. The new\napproach is demonstrated in a consistent light transport simulation algorithm\nthat uses reinforcement learning to progressively learn where light comes from.\nAs using this information for importance sampling includes information about\nvisibility, too, the number of light transport paths with zero contribution is\ndramatically reduced, resulting in much less noisy images within a fixed time\nbudget.","url_abs":"http://arxiv.org/abs/1701.07403v2","url_pdf":"http://arxiv.org/pdf/1701.07403v2.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":"learning-light-transport-the-reinforced-way","repo_url":"https://github.com/johnmave126/rl-tracing","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"learning-light-transport-the-reinforced-way","repo_url":"https://github.com/yohkaz/BasicRayTracer","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"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"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}