{"id":"W2169517535","doi":"10.1109/iros.2008.4650761","title":"Reactive planning as a motivational source in a behavior-based architecture","year":2008,"lang":"en","type":"article","venue":"","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Planner; Computer science; Component (thermodynamics); Architecture; Action selection; Task (project management); Context (archaeology); Robot; Human–computer interaction; Distributed computing; Control (management); Artificial intelligence; Engineering; Systems engineering; Perception","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007228085,0.0003743505,0.0001812818,0.0003290708,0.0005207319,0.0008794197,0.001093686,0.0005272753,0.003147708],"category_scores_gemma":[0.001109749,0.0003578748,0.0003432544,0.0002577895,0.001317672,0.001379829,0.0008678723,0.0008324245,0.000534606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007607423,"about_ca_system_score_gemma":0.001321031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00362022,"about_ca_topic_score_gemma":0.004640183,"domain_scores_codex":[0.9997155,0.00009085444,0.00001358171,0.00006269497,0.00008943291,0.00002791025],"domain_scores_gemma":[0.9996499,0.0001245646,0.00003826044,0.00005830493,0.00007482697,0.00005410178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001637997,0.0002257985,0.00161098,0.0002371259,0.00007111117,0.0003707828,0.001463258,0.3394915,0.05900096,0.4794328,0.002563907,0.1153681],"study_design_scores_gemma":[0.00003861127,0.00009467539,0.0004775207,0.0000288009,0.00003833638,0.00006397528,0.0001056246,0.8579859,0.009494732,0.1185681,0.01307642,0.00002728565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02359739,0.00008375115,0.9610419,0.0005044509,0.00002802226,0.0000993487,0.0000252303,0.001151145,0.01346884],"genre_scores_gemma":[0.4090467,0.0001759709,0.5802779,0.0001797141,0.00002459798,0.0002363275,0.00009452563,0.0001328472,0.009831465],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00362022,"threshold_uncertainty_score":0.01053017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02435600522161216,"score_gpt":0.2530631455177738,"score_spread":0.2287071402961616,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}