{"id":"W1486612343","doi":"10.1007/978-3-540-24840-8_31","title":"Multi-agent Trail Making for Stigmergic Navigation","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Maxima and minima; Construct (python library); Artificial intelligence; Terrain; Human–computer interaction; Cartography; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00096404,0.0005888035,0.0005409388,0.0006527476,0.0003669501,0.0005414246,0.003226135,0.0003650532,0.000007624521],"category_scores_gemma":[0.0001097306,0.000571567,0.0001833642,0.0005213125,0.0004380842,0.000558363,0.000659968,0.0006871821,0.00003728967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006969115,"about_ca_system_score_gemma":0.0008405002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001284539,"about_ca_topic_score_gemma":0.000006861978,"domain_scores_codex":[0.995765,0.0000260704,0.0006132138,0.00179189,0.0009763929,0.000827416],"domain_scores_gemma":[0.9975649,0.0003950134,0.0003975424,0.001203414,0.0002732007,0.0001659477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003801484,0.00003704842,0.00001635061,0.0000906637,0.00001383107,0.0001282855,0.001342969,0.5649467,0.0001679366,0.01127386,0.00000817696,0.4219704],"study_design_scores_gemma":[0.0005643899,0.0001600915,0.0001230506,0.001178028,0.00001082041,0.00008909338,1.748328e-7,0.9156733,0.0004751332,0.08073372,0.0003107153,0.0006815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002445982,0.0003769281,0.9945108,0.000476271,0.003227892,0.0007777718,0.00001239973,0.0002698708,0.0003235488],"genre_scores_gemma":[0.03227885,0.000007358485,0.9663901,0.0006318506,0.0004261242,0.00002805874,0.00001403026,0.000042835,0.0001807997],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4212889,"threshold_uncertainty_score":0.9996736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04185727782293901,"score_gpt":0.292901665820833,"score_spread":0.251044387997894,"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."}}