{"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/randomized-prior-functions-for-deep","title":"Randomized Prior Functions for Deep Reinforcement Learning","arxiv_id":"1806.03335","date":"2018-06-08","proceeding":"NeurIPS 2018 12","authors":["Ian Osband","John Aslanides","Albin Cassirer"],"abstract":"Dealing with uncertainty is essential for efficient reinforcement learning.\nThere is a growing literature on uncertainty estimation for deep learning from\nfixed datasets, but many of the most popular approaches are poorly-suited to\nsequential decision problems. Other methods, such as bootstrap sampling, have\nno mechanism for uncertainty that does not come from the observed data. We\nhighlight why this can be a crucial shortcoming and propose a simple remedy\nthrough addition of a randomized untrainable `prior' network to each ensemble\nmember. We prove that this approach is efficient with linear representations,\nprovide simple illustrations of its efficacy with nonlinear representations and\nshow that this approach scales to large-scale problems far better than previous\nattempts.","url_abs":"http://arxiv.org/abs/1806.03335v2","url_pdf":"http://arxiv.org/pdf/1806.03335v2.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":"randomized-prior-functions-for-deep","repo_url":"https://github.com/johannah/bootstrap_dqn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"deep-reinforcement-learning","task_name":"Deep Reinforcement Learning"},{"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":"https://app.syntology.ai/?focus=1806.03335","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1806.03335"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/johannah/bootstrap_dqn","reach":null}],"summary":{"ran_fixture":1,"unverified":1},"by_repo_kind":{},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":2,"samples":[{"code_sha256_prefix":"f1cb6f95361db966","entry":"rolling_average","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"f1cb6f95361db966"}},{"code_sha256_prefix":"a667ce6b07647d3d","entry":"ptlearn","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"a667ce6b07647d3d"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}