{"event":{"id":"evt-code-as-policies-20220916","dedupe_key":"language_model_robot_policy_generation:2022-09-16:code-as-policies-uses-language-models-to-generate-executable-robot-policies","event_type":"language_model_robot_policy_generation","title":"Code as Policies uses language models to generate executable robot policies","summary":"Researchers demonstrated code-writing language models composing robot-control APIs, logic and libraries into executable policies across several real robot platforms.","occurred_at":"2022-09-16T07:17:23.000Z","published_at":"2022-09-16T07:17:23.000Z","observed_at":"2026-10-02T15:12:29.000Z","reconstructed_at":"2026-10-02T15:12:29.000Z","ingest_type":"live_world_scan","locations":null,"status":"verified","confidence":0.97,"metadata":{"actors":["Google Research","collaborators"],"what_happened_at_time":"Language models generated executable control programs rather than only natural-language action descriptions.","evidence_at_time":"The September 16 arXiv preprint documents program synthesis, recursive function definition, API composition and real-robot demonstrations.","affected_layers":["layer-models","layer-robotics","layer-agents","layer-software","layer-research"],"change_kind":"tool_and_action_composition_maturation","q2_continuity":"Q2 SayCan and Q3 Inner Monologue used model planning around predefined skills; Code as Policies moved more control structure into generated code.","retrospective_inference":"Generated programs made software/API composition a more explicit bridge between models and physical action.","uncertainty":"Correctness and safety depended on APIs, perception, prompt examples and bounded robot environments; the later November Google blog is excluded from Q3 provenance.","date_normalization":"Only the 2022-09-16 arXiv preprint is treated as Q3 publication evidence."},"created_at":"2026-10-02T16:08:16.246Z","updated_at":"2026-10-02T16:08:16.246Z"},"artifacts":[{"id":"art-code-as-policies-20220916","canonical_url":"https://arxiv.org/abs/2209.07753","artifact_type":"paper_preprint","title":"Code as Policies","summary":"The paper demonstrated code-writing language models generating robot policy programs that compose APIs, logic and third-party libraries across multiple real robot platforms.","creator_entities":["Google Research and collaborators"],"released_at":"2022-09-16T07:17:23.000Z","content_hash":null,"metadata":{"historical_scope":"2022-Q3","date_note":"Only the September 16 arXiv preprint is used as contemporaneous Q3 evidence; the later Google explanatory blog is excluded from Q3 publication provenance."},"created_at":"2026-10-02T16:08:16.237Z","updated_at":"2026-10-02T16:08:16.237Z","relation":"evidenced_by"}],"signals":[{"id":"sig-q3-embodied-closed-loop-agency","statement":"LLM-mediated robotics progressed toward closed-loop replanning and executable program synthesis over robot APIs, strengthening embodied agent-like capability without establishing general persistent autonomy.","signal_type":"embodied_agent_capability_maturation","direction":"increasing","confidence":0.95,"epistemic_status":"supported_inference","mapping_mode":"retrospective","reconstructed_at":"2026-10-02T15:12:29.000Z","created_at":"2026-10-02T16:08:16.251Z","updated_at":"2026-10-02T16:08:16.251Z"}]}