{"id":"W2043433267","doi":"10.1109/cisda.2012.6291511","title":"Cooperation through mediation in multi-robot pursuit games","year":2012,"lang":"en","type":"article","venue":"","topic":"Guidance and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Ranking (information retrieval); Mediation; Task (project management); Computer science; Robot; Space (punctuation); Inference; Artificial intelligence; Autonomy; Machine learning; Goal pursuit; Process (computing); Mechanism (biology); Human–computer interaction; Psychology; Engineering; Social psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001096981,0.0000592374,0.00007999077,0.00002300961,0.00001086997,0.00001772377,0.00004129588,0.00004542028,0.00005912511],"category_scores_gemma":[0.00001375133,0.00005221923,0.00001347792,0.0000761415,0.000003455559,0.0004041535,0.000004165492,0.00004190514,0.0001913695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003673154,"about_ca_system_score_gemma":0.000003221553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007467719,"about_ca_topic_score_gemma":0.0002546741,"domain_scores_codex":[0.9995794,0.00001200378,0.0001344201,0.00004721931,0.00007035141,0.0001565931],"domain_scores_gemma":[0.9998701,0.00001275273,0.000008935159,0.00007368623,0.00001257292,0.00002201656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001954903,0.0003288049,0.2612562,0.0002321434,0.0001141371,0.000004151765,0.01718393,0.2651136,0.3677779,0.02237456,0.01739162,0.04820341],"study_design_scores_gemma":[0.003508321,0.00004216911,0.3277272,0.0000688588,0.00001863046,0.000007768353,0.001076182,0.5850906,0.03043244,0.00008069784,0.05118383,0.0007632663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5200765,0.00553421,0.4343269,0.0003674274,0.002692013,0.0006918487,0.000003139757,0.0007382797,0.03556961],"genre_scores_gemma":[0.9984814,0.0000368871,0.0008342073,0.00006500314,0.0001675151,0.0000436351,0.000006603708,0.000009860897,0.000354914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4784048,"threshold_uncertainty_score":0.2459732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02623239276878795,"score_gpt":0.2489781752890987,"score_spread":0.2227457825203107,"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."}}