Self-organization of distributedly represented multiple behavior schemata in a mirror system: reviews of robot experiments using RNNPB

Authors:
Jun Tani;Masato Ito;Yuuya Sugita
Affiliations:
Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan;Sony Corp., Gotanda, Shinagawa-ku, Tokyo, Japan;Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan
Venue:
Neural Networks - 2004 Special issue: New developments in self-organizing systems
Year:
2004

Citing 18
Cited 23

A menu of designs for reinforcement learning over time

Neural networks for control
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations

Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Distributed representations

Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Learning internal representations by error propagation

Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
The Induction of Dynamical Recognizers

Machine Learning - Connectionist approaches to language learning
A dynamical systems perspective on agent-environment interaction

Artificial Intelligence - Special volume on computational research on interaction and agency, part 1
Learning to perceive the world as articulated: an approach for hierarchical learning in sensory-motor systems

Proceedings of the fifth international conference on simulation of adaptive behavior on From animals to animats 5
Multiple paired forward and inverse models for motor control

Neural Networks - Special issue on neural control and robotics: biology and technology
A self-supervised learning system for pattern recognition by sensory integration

Neural Networks
Multiple model-based reinforcement learning

Neural Computation
The mirror system, imitation, and the evolution of language

Imitation in animals and artifacts
Imitation as a dual-route process featuring predictive and learning components: a biologically plausible computational model

Imitation in animals and artifacts
Articulation of sensory-motor experiences by "forwarding forward model": from robot experiments to phenomenology

ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Learning to generate articulated behavior through the bottom-up and the top-down interaction processes

Neural Networks
Learning Movement Sequences from Demonstration

ICDL '02 Proceedings of the 2nd International Conference on Development and Learning
MOSAIC Model for Sensorimotor Learning and Control

Neural Computation
Self-organization of behavioral primitives as multiple attractor dynamics: A robot experiment

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Incremental learning of complex temporal patterns

IEEE Transactions on Neural Networks

2006 Special issue: Mirror neurons and imitation: A computationally guided review

Neural Networks - 2006 Special issue: The brain mechanisms of imitation learning
Learning Multiple Goal-Directed Actions Through Self-Organization of a Dynamic Neural Network Model: A Humanoid Robot Experiment

Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Coordinating with the Future: The Anticipatory Nature of Representation

Minds and Machines
Schema-Based Design and the AKIRA Schema Language: An Overview

Anticipatory Behavior in Adaptive Learning Systems
Acquiring a Functionally Compositional System of Goal-Directed Actions of a Simulated Agent

SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Neural Model for the Visual Recognition of Goal-Directed Movements

ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Timed trajectory generation using dynamical systems: Application to a Puma arm

Robotics and Autonomous Systems
2009 Special Issue: Cross-modal and scale-free action representations through enaction

Neural Networks
Towards a neurocomputational model of speech production and perception

Speech Communication
Autonomy of Self at Criticality: The Perspective from Synthetic Neuro-Robotics

Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Reinforcement learning of multiple tasks using parametric bias

IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A simple model of cortical activations during both observation and execution of reach-to-grasp movements

ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Imitation learning from unsegmented human motion using switching autoregressive model and singular vector decomposition

ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Robot trajectory prediction and recognition based on a computational mirror neurons model

ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
Considerations for a neuroscience-inspired approach to the design of artificial intelligent systems

AGI'11 Proceedings of the 4th international conference on Artificial general intelligence
Simultaneously emerging Braitenberg codes and compositionality

Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Periodic motion control by modulating CPG parameters based on time-series recognition

ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Imitating others by composition of primitive actions: A neuro-dynamic model

Robotics and Autonomous Systems
CPG modulation for navigation and omnidirectional quadruped locomotion

Robotics and Autonomous Systems
Regularization and stability in reservoir networks with output feedback

Neurocomputing
Computational modeling of observational learning inspired by the cortical underpinnings of human primates

Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Sensorimotor domain approach for artificial autonomous cognitive development

SBIA'12 Proceedings of the 21st Brazilian conference on Advances in Artificial Intelligence
Emergence of multi-step discrete state transition through reinforcement learning with a recurrent neural network

ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

The current paper reviews a connectionist model, the recurrent neural network with parametric biases (RNNPB), in which multiple behavior schemata can be learned by the network in a distributed manner. The parametric biases in the network play an essential role in both generating and recognizing behavior patterns. They act as a mirror system by means of self-organizing adequate memory structures. Three different robot experiments are reviewed: robot and user interactions; learning and generating different types of dynamic patterns; and linguistic-behavior binding. The hallmark of this study is explaining how self-organizing internal structures can contribute to generalization in learning, and diversity in behavior generation, in the proposed distributed representation scheme.