{"id":"W2029155741","doi":"10.1109/siu.2010.5651543","title":"When does feedback not increase capacity for channels with memory?","year":2010,"lang":"en","type":"article","venue":"","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Independent and identically distributed random variables; Markov process; Symmetry (geometry); Markov chain; Finite state; Topology (electrical circuits); Channel (broadcasting); Channel capacity; Control theory (sociology); Distributed computing; Algorithm; Theoretical computer science; Mathematics; Random variable; Computer network; Artificial intelligence; Machine learning; Combinatorics; Statistics","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":[0.002352853,0.00053922,0.001315036,0.0005681268,0.0008627068,0.001668577,0.001504687,0.001810445,0.006859628],"category_scores_gemma":[0.03290321,0.0003948228,0.0005718363,0.0004285843,0.00245893,0.006834935,0.00165959,0.001661827,0.0004856254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001370937,"about_ca_system_score_gemma":0.001407728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001449774,"about_ca_topic_score_gemma":0.001204339,"domain_scores_codex":[0.9985306,0.0003861807,0.00006748667,0.000227278,0.0002505135,0.0005378523],"domain_scores_gemma":[0.971742,0.02206007,0.002055757,0.001784528,0.001261402,0.0010963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001863077,0.0004449478,0.004575525,0.0009653237,0.000180907,0.0009416549,0.0004357994,0.2941146,0.0314004,0.5118064,0.01191864,0.1413526],"study_design_scores_gemma":[0.0001735522,0.0004164623,0.001403868,0.0001145599,0.00007287443,0.0004720005,0.000316551,0.5404487,0.0161265,0.4378108,0.002545895,0.00009825404],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.558755,0.001389247,0.4071966,0.008721784,0.0005029432,0.000160769,0.0007381269,0.001539748,0.02099573],"genre_scores_gemma":[0.9911277,0.0002005976,0.007042568,0.0002704987,0.00008763785,0.00005114358,0.00003805528,0.00006575325,0.001116054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006859628,"threshold_uncertainty_score":0.02294773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01784659395454224,"score_gpt":0.2266135529101748,"score_spread":0.2087669589556326,"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."}}