LEADER 08223nam 2200517 450 001 996490364803316 005 20230206223555.0 010 $a3-031-16770-8 035 $a(MiAaPQ)EBC7083173 035 $a(Au-PeEL)EBL7083173 035 $a(CKB)24814907600041 035 $a(PPN)264953185 035 $a(EXLCZ)9924814907600041 100 $a20230206d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aFrom animals to animats 16 $e16th international conference on simulation of adaptive behavior, SAB 2022, Cergy-Pontoise, France, September 20-23, 2022 : proceedings /$fLola Can?amero [and four others], editors 210 1$aCham, Switzerland :$cSpringer Nature Switzerland AG,$d[2022] 210 4$d©2022 215 $a1 online resource (225 pages) 225 1 $aLecture Notes in Arti?cial Intelligence 311 08$aPrint version: Cañamero, Lola From Animals to Animats 16 Cham : Springer International Publishing AG,c2022 9783031167690 320 $aIncludes bibliographical references and index. 327 $aIntro -- Preface -- Organization -- Contents -- Embodiment -- How to Design Morphologies. A Design Process for Autonomous Robots -- 1 Introduction -- 2 Proposal of a Design Process -- 2.1 Arc Representation -- 2.2 Morphological Manifold as a Directed Graph -- 2.3 Algorithmically Determined Motion Sequences -- 2.4 Plug'n'Clamp Kit -- 3 Evaluation -- 4 Discussion and Outlook -- References -- Exploring Sensitization in the Context of Extending the Behavior of an Artificial Agent -- 1 Introduction -- 2 Sensitization -- 3 IDSM -- 4 Model of Pseudo-conditioning Through Generalization of Nodes -- 5 Experiments and Results -- 5.1 Setup -- 5.2 Results -- 6 Discussion -- References -- Investigating a Minimal Categorical Perception Task with a Node-Based Sensorimotor Map -- 1 Introduction -- 2 Model -- 2.1 NB-SMM -- 2.2 Experiment Setup -- 2.3 CTRNN Comparison -- 3 Results -- 3.1 NB-SMM Results -- 3.2 Categorical Perception -- 3.3 CTRNN Results -- 4 Discussion -- References -- Deep Gaussian Processes for Angle and Position Discrimination in Active Touch Sensing -- 1 Introduction -- 2 Methods -- 2.1 Dataset -- 2.2 Dimensionality Reduction -- 2.3 Gaussian Process Based Models -- 3 Results -- 3.1 Position Discrimination -- 3.2 Angle Discrimination -- 4 Discussion and Future Work -- References -- Neural Body Bending Control with Temporal Delays for Millipede-Like Turning Behaviour of a Multi-segmented, Legged Robot -- 1 Introduction -- 2 Materials and Methods -- 2.1 Millipede-Inspired Robot -- 2.2 Neural Control System for Millipede-Like Turning Behaviour -- 2.3 Neural Body Bending Control with Temporal Delays -- 3 Experiments and Results -- 3.1 Millipede-Like Turning Behaviour -- 3.2 Navigation in Different Environments with Narrow Paths -- 4 Conclusion -- References -- Brain-Inspired Control, Adaptation, and Learning. 327 $aYoking-Based Identification of Learning Behavior in Artificial and Biological Agents -- 1 Introduction -- 2 Related Work -- 3 Comparing Synthetic Learning Models to Target Data -- 3.1 Problem Formalization -- 3.2 Unconstrained Approach to Identify Learning Algorithms -- 3.3 Yoked Approach to Identify Learning Algorithms -- 4 Evaluation in a Synthetic Lockbox Task -- 4.1 Identifying Known Ground Truth Learning Algorithms -- 4.2 Comparison over Size of Action Space -- 5 Evaluation in a Real Cockatoo Lockbox Learning Task -- 6 Conclusion -- References -- Is Free Energy an Organizational Principle in Spiking Neural Networks? -- 1 Introduction: Decoding the Free Energy Concept -- 2 Free Energy in the Absence of External Sensing -- 3 Non-variational Free Energy in a Spiking Neural Network -- 4 Conclusions -- 5 Supplemental Information -- References -- Create Efficient and Complex Reservoir Computing Architectures with ReservoirPy -- 1 Introduction -- 2 Flexible Reservoir Computing -- 2.1 Functional Nodes -- 2.2 Learning Rules -- 2.3 Models as Computational Graphs -- 2.4 Feedback Loops -- 3 Getting Started: ESN for Timeseries Forecasting with ReservoirPy -- 3.1 Step 1: Choose a Timeseries for One Timestep Ahead Prediction -- 3.2 Step 2: Define Your ESN -- 3.3 Step 3.1: Train the Offline Model -- 3.4 Step 3.2: Train the Online Model -- 3.5 Step 4: Evaluate the Model -- 4 Discussion -- References -- Adaptive Inhibition for Optimal Energy Consumption by Animals, Robots and Neurocomputers -- 1 Introduction -- 1.1 Specific and Non-specific Inhibition in Animals -- 1.2 The Quality of Cognitive Processes -- 2 Energy Measurements in a Physical System -- 3 Adaptive Inhibition -- 4 Discussion -- References -- Adapting to Environment Changes Through Neuromodulation of Reinforcement Learning -- 1 Introduction -- 2 Problem -- 2.1 Reinforcement Learning. 327 $a2.2 Environment Changes -- 3 Method -- 3.1 ACh and NE Neuromodulation -- 3.2 Update of ACh and NE System -- 3.3 The Complete System -- 4 Experiments -- 5 Results -- 5.1 Reinforcement Learning Performance -- 5.2 Activity of Neuromodulatory System -- 6 Conclusion -- References -- Multi-task Learning with Modular Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Reinforcement Learning -- 3.2 Modular Reinforcement Learning -- 4 The Inverse Arbi-Q Architecture -- 5 Implementation -- 5.1 State Predictor -- 5.2 Reward Predictor -- 5.3 RL Controller -- 5.4 Action Selection -- 6 Simulation -- 6.1 Settings -- 6.2 Results -- 7 Conclusions and Future Work -- References -- Bio-inspired Vision and Navigation -- Same/Different Concept: An Embodied Spiking Neural Model in a Learning Context -- 1 Introduction -- 2 Methodology -- 2.1 Protocol -- 2.2 Neural Architecture -- 2.3 Physical Environment -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Sparse and Topological Coding for Visual Localization of Autonomous Vehicles -- 1 Introduction -- 2 Related Work: Definition of the Sparse Coding -- 3 Topological Sparse Coding -- 4 SMP Model -- 5 Materials and Methods -- 5.1 Dataset -- 5.2 Metrics -- 5.3 Evaluation Methodology -- 5.4 Implementation Details -- 6 Results -- 6.1 Properties of TSC During Learning -- 6.2 Evaluation of Configuration/Performance -- 6.3 Evaluation of Localization Performances with the State of the Art -- 7 Discussion and Conclusion -- References -- Contribution of the Retrosplenial Cortex to Path Integration and Spatial Codes -- 1 Introduction -- 2 Computational Model -- 3 Experiment and Results -- 3.1 Recording ot Neurons Learning MD Activities in RSC -- 3.2 Building Place Cells from PI Information -- 3.3 Robustness of the Model -- 4 Conclusion and Perspective -- References. 327 $aFlexible Path Planning in a Spiking Model of Replay and Vicarious Trial and Error -- 1 Introduction -- 2 Methods -- 2.1 Spiking Wave Propagation -- 2.2 E-Prop and Back-Propagation Through Time -- 2.3 Extracting a Path from the Spike Wavefront Algorithm -- 3 Results -- 3.1 Simulating Human Navigation and Taking Novel Shortcuts -- 3.2 Simulating Rodent Navigation in Tolman Detour Task -- 4 Discussion -- References -- Affective and Social Cognition and Collective Intelligence -- Impact of the Update Time on the Aggregation of Robotic Swarms Through Informed Robots -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 4 Conclusions -- References -- On the Adaptive Value of Mood and Mood Contagion -- 1 Introduction -- 2 Agent Model -- 3 Reference Mood Experiments -- 4 Evolution of Mood -- 5 Mood Contagion -- 6 Evolution of Mood Contagion -- 7 Discussion -- References -- Author Index. 410 0$aLecture notes in computer science.$pLecture notes in artificial intelligence. 606 $aComputer vision$vCongresses 606 $aAdaptive computing systems 606 $aRobotics$vCongresses 615 0$aComputer vision 615 0$aAdaptive computing systems. 615 0$aRobotics 676 $a004 702 $aCan?amero$b Lola 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996490364803316 996 $aFrom animals to animats 16$93009052 997 $aUNISA