From Animals to Animats 13

1. Front Matter

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2. Animat Approach and Methodology

   1. A Role for Sleep in Artificial Cognition through Deferred Restructuring of Experience in Autonomous Machines

      • Richard J. Duro, Francisco Bellas, José A. Becerra, Rodrigo Salgado

      Pages 1-10

   2. Time in Consciousness, Memory and Human-Robot Interaction

      • Michail Maniadakis, Panos Trahanias

      Pages 11-20

   3. Non-representational Sensorimotor Knowledge

      • Thomas Buhrmann, Ezequiel Di Paolo

      Pages 21-31

3. Perception and Motor Control

   1. Self-exploration of the Stumpy Robot with Predictive Information Maximization

      • Georg Martius, Luisa Jahn, Helmut Hauser, Verena V. Hafner

      Pages 32-42

   2. Detecting the Vibration in the Artificial Web Inspired by the Spider

      • Eunseok Jeong, DaeEun Kim

      Pages 43-52

   3. Modelling Reaction Times in Non-linear Classification Tasks

      • Martha Lewis, Anna Fedor, Michael Öllinger, Eörs Szathmáry, Chrisantha Fernando

      Pages 53-64

   4. Multiple Decoupled CPGs with Local Sensory Feedback for Adaptive Locomotion Behaviors of Bio-inspired Walking Robots

      • Subhi Shaker Barikhan, Florentin Wörgötter, Poramate Manoonpong

      Pages 65-75

   5. The Role of a Cerebellum-Driven Perceptual Prediction within a Robotic Postural Task

      • Giovanni Maffei, Marti Sanchez-Fibla, Ivan Herreros, Paul F. M. J. Verschure

      Pages 76-87

   6. Biomimetic Agent Based Modelling Using Male Frog Calling Behaviour as a Case Study

      • Søren V. Jørgensen, Yves Demazeau, Jakob Christensen-Dalsgaard, John Hallam

      Pages 88-97

4. Navigation and Internal World Models

   1. Snapshot Homing Navigation Based on Edge Features

      • SeungMin Baek, DaeEun Kim

      Pages 98-107

   2. Ground-Nesting Insects Could Use Visual Tracking for Monitoring Nest Position during Learning Flights

      • Nermin Samet, Jochen Zeil, Elmar Mair, Norbert Boeddeker, Wolfgang Stürzl

      Pages 108-120

   3. Adaptive Landmark-Based Navigation System Using Learning Techniques

      • Bassel Zeidan, Sakyasingha Dasgupta, Florentin Wörgötter, Poramate Manoonpong

      Pages 121-131

   4. Robustness Study of a Multimodal Compass Inspired from HD-Cells and Dynamic Neural Fields

      • Pierre Delarboulas, Philippe Gaussier, Ramesh Caussy, Mathias Quoy

      Pages 132-143

5. Learning and Adaptation

   1. Developmental Dynamics of RNNPB: New Insight about Infant Action Development

      • Jun-Cheol Park, Dae-Shik Kim, Yukie Nagai

      Pages 144-153

   2. Simulating the Emergence of Early Physical and Social Interactions : A Developmental Route through Low Level Visuomotor Learning

      • Raphael Braud, Ghiles Mostafaoui, Ali Karaouzene, Philippe Gaussier

      Pages 154-165

   3. Intrinsically Motivated Decision Making for Situated, Goal-Driven Agents

      • Mohamed Oubbati, Christian Fischer, Günther Palm

      Pages 166-175

   4. An Anti-hebbian Learning Rule to Represent Drive Motivations for Reinforcement Learning

      • Varun Raj Kompella, Sohrob Kazerounian, Jürgen Schmidhuber

      Pages 176-187

   5. Unsupervised Learning of Sensory Primitives from Optical Flow Fields

      • Oswald Berthold, Verena V. Hafner

      Pages 188-197

   6. Reinforcement-Driven Shaping of Sequence Learning in Neural Dynamics

      • Matthew Luciw, Sohrob Kazerounian, Yulia Sandamirskaya, Gregor Schöner, Jürgen Schmidhuber

      Pages 198-209

This book constitutes the proceedings of the 13th International Conference on Simulation of Adaptive Behavior, SAB 2014, held in Castellón, Spain, in July 2014. The 32 papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. They cover the main areas in animat research, including the animat approach and methodology, perception and motor control, navigation and internal world models, learning and adaptation, evolution and collective and social behavior.

• cognitive robotics
• human robot interaction
• mobile ad hoc networks
• multi-agent systems
• neural networks
• reinforcement learning
• robotics
• self-organization
• simulation
• vision for robotics
• algorithm analysis and problem complexity

• Robotic Intelligence Lavoratory, Jaume I University, Castellón de la Plana, Spain

  Angel P. Pobil

• School of Computing, University of Leeds, Leeds, UK

  Eris Chinellato

• Robotic Intelligence Laboratory, Jaume I University, Castellón de la Plana, Spain

  Ester Martinez-Martin, Enric Cervera

• Mærsk McKinney Møller Institute, University of Southern Denmark, Odense, Denmark

  John Hallam

• Robotic Intelligence Laboratory, Jaume I University, Castellón de la Plana, spain

  Antonio Morales

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