{"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/prism-a-robust-framework-for-skill-based-meta","title":"PRISM: A Robust Framework for Skill-based Meta-Reinforcement Learning with Noisy Demonstrations","arxiv_id":"2502.03752","date":"2025-02-06","proceeding":null,"authors":["Sanghyeon Lee","Sangjun Bae","Yisak Park","Seungyul Han"],"abstract":"Meta-reinforcement learning (Meta-RL) facilitates rapid adaptation to unseen tasks but faces challenges in long-horizon environments. Skill-based approaches tackle this by decomposing state-action sequences into reusable skills and employing hierarchical decision-making. However, these methods are highly susceptible to noisy offline demonstrations, resulting in unstable skill learning and degraded performance. To overcome this, we propose Prioritized Refinement for Skill-Based Meta-RL (PRISM), a robust framework that integrates exploration near noisy data to generate online trajectories and combines them with offline data. Through prioritization, PRISM extracts high-quality data to learn task-relevant skills effectively. By addressing the impact of noise, our method ensures stable skill learning and achieves superior performance in long-horizon tasks, even with noisy and sub-optimal data.","url_abs":"https://arxiv.org/abs/2502.03752v1","url_pdf":"https://arxiv.org/pdf/2502.03752v1.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":[],"tasks":[{"task_slug":"decision-making","task_name":"Decision Making"},{"task_slug":"meta-reinforcement-learning","task_name":"Meta Reinforcement Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2502.03752","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2502.03752"}},"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":"deterministic:regex_extraction","url":"https://github.com/katerakelly/oyster","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"deterministic:regex_extraction","url":"https://github.com/Farama-Foundation/D4RL","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"deterministic:regex_extraction","url":"https://github.com/denisyarats/pytorch","reach":{"status":"gone","observed_at":"2026-09-17","how":"tree_404+repo_404"}},{"provenance":"deterministic:regex_extraction","url":"https://github.com/openai/random-network-distillation","reach":{"status":"ok"}},{"provenance":"deterministic:regex_extraction","url":"https://github.com/clvrai/spirl","reach":{"status":"ok"}},{"provenance":"deterministic:regex_extraction","url":"https://github.com/namsan96/SiMPL","reach":{"status":"ok"}},{"provenance":"deterministic:regex_extraction","url":"https://github.com/clvrai/skild","reach":{"status":"ok"}}],"summary":{"ran":4,"ran_draft_wrong":1,"unverified":1},"by_repo_kind":{"found_in_text":{"samples":6,"ran":5,"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":0,"samples":[{"code_sha256_prefix":"f395bfda2e4813d7","entry":"create_stats_ordered_dict","repo":"katerakelly/oyster","repo_kind":"found_in_text","path":"rlkit/core/eval_util.py","file_url":"https://github.com/katerakelly/oyster/blob/HEAD/rlkit/core/eval_util.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"f395bfda2e4813d7"}},{"code_sha256_prefix":"e937b70b07bfc9d1","entry":"deep_update_dict","repo":"katerakelly/oyster","repo_kind":"found_in_text","path":"launch_experiment.py","file_url":"https://github.com/katerakelly/oyster/blob/HEAD/launch_experiment.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"e937b70b07bfc9d1"}},{"code_sha256_prefix":"a5d10a0b704c8db7","entry":"get_average_returns","repo":"katerakelly/oyster","repo_kind":"found_in_text","path":"rlkit/core/eval_util.py","file_url":"https://github.com/katerakelly/oyster/blob/HEAD/rlkit/core/eval_util.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"a5d10a0b704c8db7"}},{"code_sha256_prefix":"c809703793017cd2","entry":"get_generic_path_information","repo":"katerakelly/oyster","repo_kind":"found_in_text","path":"rlkit/core/eval_util.py","file_url":"https://github.com/katerakelly/oyster/blob/HEAD/rlkit/core/eval_util.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c809703793017cd2"}},{"code_sha256_prefix":"5cb0c55f58279f59","entry":"simple_separated_format","repo":"katerakelly/oyster","repo_kind":"found_in_text","path":"rlkit/core/tabulate.py","file_url":"https://github.com/katerakelly/oyster/blob/HEAD/rlkit/core/tabulate.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"5cb0c55f58279f59"}},{"code_sha256_prefix":"3d87729bd4c217d5","entry":"get_mujoco_zip_name","repo":"katerakelly/oyster","repo_kind":"found_in_text","path":"docker/install_mujoco.py","file_url":"https://github.com/katerakelly/oyster/blob/HEAD/docker/install_mujoco.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"3d87729bd4c217d5"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}