{"schema_version":"onlylabs.public_signal.v1","title":"OpenAI Writing: Plan online, learn offline: Efficient learning and exploration via model-based control","description":"OpenAI writing signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/51a78e12-ed88-4ac8-af83-653f811259cd","json_url":"https://onlylabs.fyi/signals/51a78e12-ed88-4ac8-af83-653f811259cd/signal.json","generated_at":"2026-06-08T15:47:03.316+00:00","org":{"slug":"openai","name":"OpenAI","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/openai","dossier_json_url":"https://onlylabs.fyi/labs/openai/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/51a78e12-ed88-4ac8-af83-653f811259cd","signal_json":"https://onlylabs.fyi/signals/51a78e12-ed88-4ac8-af83-653f811259cd/signal.json","source":"https://openai.com/index/plan-online-learn-offline","lab_dossier":"https://onlylabs.fyi/labs/openai","lab_dossier_json":"https://onlylabs.fyi/labs/openai/dossier.json","analysis":"https://onlylabs.fyi/analysis/openai","analysis_json":"https://onlylabs.fyi/analysis/openai/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/openai/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":"https://onlylabs.fyi/topics/talking","topic_signals_json":"https://onlylabs.fyi/topics/talking/signals.json","topic_feed":"https://onlylabs.fyi/topics/talking/feed.xml","data_business":null},"answer_pack":{"answer":"OpenAI published Plan online, learn offline: Efficient learning and exploration via model-based control. This talking signal gives public context for research themes, product direction, policy, or launch framing. High-signal details: Plan online, learn offline: Efficient learning and exploration via model-based control | OpenAI November 5, 2018 Plan online, learn offline: Efficient learning and.... onlylabs links this event to 1 captured evidence page and 6 related writing signals.","signal_desk":"talking","source_context":{"source_url":"https://openai.com/index/plan-online-learn-offline","source_host":"openai.com","occurred_at":"2018-11-05T08:00:00+00:00","first_seen_at":"2026-06-05T05:42:57.832854+00:00","date_source":"rss.item_date","context":null},"context_markers":[{"label":"Lab","value":"OpenAI","source":"signal"},{"label":"Signal desk","value":"talking","source":"signal"},{"label":"Source host","value":"openai.com","source":"source"},{"label":"Watch term","value":"RL environments","source":"evidence"},{"label":"Watch term","value":"Infrastructure","source":"evidence"},{"label":"Watch term","value":"Agents and tool 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This talking signal gives public context for research themes, product direction, policy, or launch framing. High-signal details: Plan online, learn offline: Efficient learning and exploration via model-based control | OpenAI November 5, 2018 Plan online, learn offline: Efficient learning and.... onlylabs links this event to 1 captured evidence page and 6 related writing signals.","semantic_triples":[{"subject":"OpenAI","predicate":"published","object":"Plan online, learn offline: Efficient learning and exploration via model-based control","text":"OpenAI published Plan online, learn offline: Efficient learning and exploration via model-based control."},{"subject":"Plan online, learn offline: Efficient learning and exploration via model-based control","predicate":"is classified as","object":"writing signal","text":"Plan online, learn offline: Efficient learning and exploration via model-based control is classified as writing signal."},{"subject":"Plan online, learn offline: Efficient learning and exploration via model-based control","predicate":"belongs to","object":"talking desk","text":"Plan online, learn offline: Efficient learning and exploration via model-based control belongs to talking desk."},{"subject":"Plan online, learn offline: Efficient learning and exploration via model-based control","predicate":"has evidence coverage","object":"1 captured evidence page","text":"Plan online, learn offline: Efficient learning and exploration via model-based control has evidence coverage 1 captured evidence page."}]},"signal":{"id":"51a78e12-ed88-4ac8-af83-653f811259cd","url":"https://onlylabs.fyi/signals/51a78e12-ed88-4ac8-af83-653f811259cd","json_url":"https://onlylabs.fyi/signals/51a78e12-ed88-4ac8-af83-653f811259cd/signal.json","source_url":"https://openai.com/index/plan-online-learn-offline","title":"Plan online, learn offline: Efficient learning and exploration via model-based control","summary":"OpenAI published a writing signal. onlylabs watches public writing for research themes, product direction, and model-launch context.","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"openai","name":"OpenAI","category":"frontier-lab"},"occurred_at":"2018-11-05T08:00:00+00:00","first_seen_at":"2026-06-05T05:42:57.832854+00:00","date_source":"rss.item_date","evidence_coverage":{"target_pages":1,"captured_pages":1,"readable_pages":1,"capture_methods":["exa"],"missing_page_urls":[],"failed_page_urls":[],"blocked_page_urls":[],"page_urls":["https://openai.com/index/plan-online-learn-offline"]},"facets":{},"traction":{"github_stars":null,"hn_points":null,"hn_comments":null,"hn_story_id":null,"hf_downloads":null,"hf_likes":null},"data_radar":null},"primary_evidence_page":{"url":"https://openai.com/index/plan-online-learn-offline","final_url":"https://openai.com/index/plan-online-learn-offline","title":"Plan online, learn offline: Efficient learning and exploration via model-based control","http_status":200,"content_type":null,"capture_method":"exa","fetched_at":"2026-06-08T15:47:03.316+00:00","bytes":null,"raw_path":null,"content_hash":null,"excerpt_chars":1200,"truncated":true,"excerpt":"Plan online, learn offline: Efficient learning and exploration via model-based control | OpenAI November 5, 2018 Plan online, learn offline: Efficient learning and exploration via model-based control Loading… Share Abstract We propose a plan online and learn offline (POLO) framework for the setting where an agent, with an internal model, needs to continually act and learn in the world. Our work builds on the synergistic relationship between local model-based control, global value function learning, and exploration. We study how local trajectory optimization can cope with approximation errors in the value function, and can stabilize and accelerate value function learning. Conversely, we also study how approximate value functions can help reduce the planning horizon and allow for better policies beyond local solutions. Finally, we also demonstrate how trajectory optimization can be used to perform temporally coordinated exploration in conjunction with estimating uncertainty in value function approximation. This exploration is critical for fast and stable learning of the value function. Combining these components enable solutions to complex simulated control tasks, like humanoid..."},"evidence_pages":[{"url":"https://openai.com/index/plan-online-learn-offline","final_url":"https://openai.com/index/plan-online-learn-offline","title":"Plan online, learn offline: Efficient learning and exploration via model-based control","http_status":200,"content_type":null,"capture_method":"exa","fetched_at":"2026-06-08T15:47:03.316+00:00","bytes":null,"raw_path":null,"content_hash":null,"excerpt_chars":1200,"truncated":true,"excerpt":"Plan online, learn offline: Efficient learning and exploration via model-based control | OpenAI November 5, 2018 Plan online, learn offline: Efficient learning and exploration via model-based control Loading… Share Abstract We propose a plan online and learn offline (POLO) framework for the setting where an agent, with an internal model, needs to continually act and learn in the world. Our work builds on the synergistic relationship between local model-based control, global value function learning, and exploration. We study how local trajectory optimization can cope with approximation errors in the value function, and can stabilize and accelerate value function learning. Conversely, we also study how approximate value functions can help reduce the planning horizon and allow for better policies beyond local solutions. Finally, we also demonstrate how trajectory optimization can be used to perform temporally coordinated exploration in conjunction with estimating uncertainty in value function approximation. This exploration is critical for fast and stable learning of the value function. 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