Work notes
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smp autosummary snapshot 2019-05-17
Approach (2), Methods and framework (3), Contributions (4), Ansatz (6), Methoden und Rahmen (7), The engineering black box (1), AI history (2), AI state of the art (3), Sensorimotor learning in humans (4), Sensorimotor learning for robots (5), Robot learning problem (6), Problem statement (7), Quadrotor (8), Adaptive stabilization (9), Bootstrap reduction (10), Approach summary (11), AI (12), Bio-inspired AI (13), Agents (14), Developmental robotics (15), Adaptation (16), Embodiment (17), Self-exploration (18), Theory (19), Structure Self-exploration (20), Structure Skill-acquisition (21), Contributions (22), Summary (23), Single-words summary (24), Enactive theory (25), Sensorimotor account of cognition (26), Sensorimotor contingencies (27), Behavior (28), Sensorimotor loop (29), Sensorimotor space (30), Observer- dependence (31), Active behavior and energy (32), Information flow (33), Quantified information flow (34), Adaptive behavior (35), Adaption level (36), Machine learning (37), Autonomous learning (38), Internal models (39), Neuroscience (40), Bio-plausibility (41), Reflex arcs and motion primitives (42), Machine learning and statistics (43), Algorithmic priors (44), Intrinsic motivation (46), Exploration (47), Adequacy (48), Agent model (49), Embodied interaction (50), Interaction topology (51), Cut (52), Predictive processing (53), Proprioceptive grounding (54), Agent- environment interaction example (55), Self-exploration (56), Skill acquisition (57), Self-exploration and skill acquisition (58), Learning problem (61), Agent recap (62), Developmental models (63), Multiple models (64), Motivation and goals (65), Model interaction (66), Introspection (67), Fitness and goals (68), Summary (69), Problem examples (70), Software library (71), smp_graphs README (72), Summary (73), Terminology (74), World and agent state (75), Channel (78), Strategy (79), System (80), Uniform random strategy (81), Baseline result (82), Random walks (83), smp_expr0000 description (84), smp_expr0000 equation (85), smp_expr0010 description (86), smp_expr0020 description (87), smp_expr0030 description (88), Baseline summary (89), Divergence factors (90), External entropy (91), Divergence measures (92), Entropic measures (93), smp_expr0045 description (94), smp_expr0046 description (95), expr0046 summary (96), smp_expr0050 description (97), smp_expr0050 description (98), Divergence summary (99), Summary (100), Internal models historically (101), Internal models current (102), Learning models (104), Model function (105), Model learning examples (106), smp_expr0060 description (107), smp_expr0061 description (108), Intermodal maps (109), smp_expr0062 description (110), end-expr (111), Delay (112), smp_expr0063 description (113), Reward and prediction error (114), Motivation (115), smp_expr0064 description (116), Sensorimotor framework summary (117), Conclusion (118), Summary (119), Exploration (120), Self (121), Self-exploration (122), Learning as modelling (123), Signal processing (125), Modelling tools (126), Information theory (127), Sensorimotor space (129), Column structure (130), Row structure (131), Time (132), Modality (133), Forward change (134), Backward change (135), Tappings summary (136), Variations (137), Simple predictor (138), Autoencoder (139), Auto-Predictive- Encoder (140), Reinforcement learning (142), Neuroscience (143), Recurrence and autoregression (144), Info loss (145), Summary (146), Summary (147), Main idea (148), Scanning (149), smp_expr0100 description (150), Cross-correlation (151), smp_expr0110 description (152), smp_expr0111 description (153), Information theory (154), Entropy (155), Mutual information (156), Predictive information (157), Transfer entropy (158), Related work (159), Information decomposition (160), Mutual information scanning (161), Differint (162), smp_expr0120 description (163), More experiments (164), smp_expr0130 description (165), smp_expr0131 description (166), smp_expr0132 description (167), Sliding window (168), smp_expr0150 description (169), Individual variables (170), description (161), smp_expr0165 description (172), Generalized CMI (173), Open issues (174), Qtap summary (175), SMP approach (179), SMP models (180), IMP training batch (183), Batch learning issues (184), IMP training online (185), IMP - dm-imol model family (186), IMP - dm-imol model family low-level algorithms (187), IMP - dm-imol call graph (188), IMP - dm-imol tapping (189), smp_expr0300 description (191), dm_imol plot description (192), IMP - dm-imol variations and summary (193), Beyond internal model pairs (194), Active inference (195), Leveraging the interpretation (196), actinf model (197), actinf algorithm and callgraph (198), smp_dm description (199), smp_expr0400 description (200), Hebbian learning (201), Reward modulation (202), Value functions (203), smp EH model and extension (204), Reservoir online learning (205), Model equation (207), Update details (206), Target synthesis (208), Update equations (209), Performance definition (210), Learning rule (211), smp_dm description (212), smp_expr0500 description (213), Skill acquisition summary (214), Skill acquisition result comparison (215), Measures 1 (216), Measures 2 (217), Summary (218), Summary (219), Problem (220), Approach (221), Contributions (222), Solution (223), Technical (224), Exploration (225), Growth and hierarchy (226), Growth and resources (227), Resources (228), Physiology (229), Consolidation (230), Problem conclusion (231), Problem statement outlook (232), Frame problem (234), Limitation as resource (235), Scaling it up (236), End-to-end ratio (237), Point mass (239), Summary (240), Summary (241), Abstract (242), Results (243), Summary (244).
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