{"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/a-low-cost-ethics-shaping-approach-for","title":"A Low-Cost Ethics Shaping Approach for Designing Reinforcement Learning Agents","arxiv_id":"1712.04172","date":"2017-12-12","proceeding":null,"authors":["Yueh-Hua Wu","Shou-De Lin"],"abstract":"This paper proposes a low-cost, easily realizable strategy to equip a\nreinforcement learning (RL) agent the capability of behaving ethically. Our\nmodel allows the designers of RL agents to solely focus on the task to achieve,\nwithout having to worry about the implementation of multiple trivial ethical\npatterns to follow. Based on the assumption that the majority of human\nbehavior, regardless which goals they are achieving, is ethical, our design\nintegrates human policy with the RL policy to achieve the target objective with\nless chance of violating the ethical code that human beings normally obey.","url_abs":"http://arxiv.org/abs/1712.04172v2","url_pdf":"http://arxiv.org/pdf/1712.04172v2.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":"a-low-cost-ethics-shaping-approach-for","repo_url":"https://github.com/kristery/EthicsShaping","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"ethics","task_name":"Ethics"},{"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=1712.04172","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1712.04172"}},"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/kristery/EthicsShaping","reach":null}],"summary":{"ran_violates":1},"by_repo_kind":{"listed":{"samples":1,"ran":1,"repositories":1}},"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":1,"samples":[{"code_sha256_prefix":"545fcc23b912f1c1","entry":"kl_div","repo":"kristery/EthicsShaping","repo_kind":"listed","path":"Drive/sarsa.py","file_url":"https://github.com/kristery/EthicsShaping/blob/HEAD/Drive/sarsa.py","link_basis":"first_harvest_node","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"545fcc23b912f1c1"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}