{"id":"W3196677378","doi":"10.3390/electronics10172136","title":"Agent in a Box: A Framework for Autonomous Mobile Robots with Beliefs, Desires, and Intentions","year":2021,"lang":"en","type":"article","venue":"Electronics","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Variety (cybernetics); Mobile robot; Semantic reasoner; Human–computer interaction; Domain (mathematical analysis); Computer science; Artificial intelligence; Resource (disambiguation); Embedded system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002146698,0.00131624,0.0009498463,0.0009319129,0.00116886,0.002891579,0.003079996,0.002338434,0.008073309],"category_scores_gemma":[0.001980739,0.001329859,0.002230913,0.0005692388,0.002208697,0.003155126,0.003054157,0.003232345,0.002823375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007019245,"about_ca_system_score_gemma":0.002021317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005028517,"about_ca_topic_score_gemma":0.006555197,"domain_scores_codex":[0.9992852,0.0002401595,0.00007782535,0.0001033297,0.0002227093,0.00007087822],"domain_scores_gemma":[0.9994222,0.0002977452,0.00004895452,0.00008927562,0.00007064903,0.00007118067],"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":[0.0001447935,0.0001243676,0.0004798729,0.0007416539,0.0001159001,0.0007932022,0.001303821,0.08191749,0.007320452,0.8038127,0.01109109,0.09215463],"study_design_scores_gemma":[0.0001559164,0.0001434595,0.000192116,0.0004079413,0.0001065547,0.0006878446,0.0002199342,0.3735781,0.005943623,0.2147759,0.4036637,0.0001249027],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004086283,0.0001524596,0.9949551,0.0001174951,0.0000509429,0.0001008707,0.00007035009,0.001904763,0.002239347],"genre_scores_gemma":[0.01806319,0.0005465942,0.9744502,0.0001521585,0.00004139268,0.0006354115,0.0003148282,0.00060327,0.005192935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008073309,"threshold_uncertainty_score":0.02700788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01698039838325497,"score_gpt":0.2658396605072492,"score_spread":0.2488592621239943,"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."}}