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Featured Co-authors

Stefan Wermter
125 publications
Dongsheng Li
104 publications
Cornelius Weber
43 publications
Tetsuya Ogata
31 publications
Beren Millidge
28 publications
Christopher L. Buckley
26 publications
Angelo Cangelosi
24 publications
Pablo Lanillos
23 publications
German I. Parisi
18 publications
Alexander Tschantz
16 publications
Kenji Doya
13 publications

research

∙ 04/11/2023

Habits and goals in synergy: a variational Bayesian framework for behavior

How to behave efficiently and flexibly is a central problem for understa...

0 Dongqi Han, et al. ∙

research

∙ 03/27/2023

Human-Robot Kinaesthetic Interaction Based on Free Energy Principle

The current study investigated possible human-robot kinaesthetic interac...

0 Hiroki Sawada, et al. ∙

research

∙ 05/05/2022

Morphological Wobbling Can Help Robots Learn

We propose to make the physical characteristics of a robot oscillate whi...

0 Fabien C. Y. Benureau, et al. ∙

research

∙ 02/26/2022

Initialization of Latent Space Coordinates via Random Linear Projections for Learning Robotic Sensory-Motor Sequences

Robot kinematics data, despite being a high dimensional process, is high...

0 Vsevolod Nikulin, et al. ∙

research

∙ 02/21/2022

Goal-directed Planning and Goal Understanding by Active Inference: Evaluation Through Simulated and Physical Robot Experiments

We show that goal-directed action planning and generation in a teleologi...

0 Takazumi Matsumoto, et al. ∙

research

∙ 12/03/2021

Active Inference in Robotics and Artificial Agents: Survey and Challenges

Active inference is a mathematical framework which originated in computa...

19 Pablo Lanillos, et al. ∙

research

∙ 11/04/2021

Sensory attenuation develops as a result of sensorimotor experience

The brain attenuates its responses to self-produced exteroceptions (e.g....

0 Hayato Idei, et al. ∙

research

∙ 06/18/2021

Goal-Directed Planning by Reinforcement Learning and Active Inference

What is the difference between goal-directed and habitual behavior? We p...

13 Dongqi Han, et al. ∙

research

∙ 03/03/2021

Controlling the Sense of Agency in Dyadic Robot Interaction: An Active Inference Approach

This study investigated how social interaction among robotic agents chan...

0 Nadine Wirkuttis, et al. ∙

research

∙ 02/18/2021

Learning Memory-Dependent Continuous Control from Demonstrations

Efficient exploration has presented a long-standing challenge in reinfor...

0 Siqing Hou, et al. ∙

research

∙ 10/28/2020

Morphological Development at the Evolutionary Timescale: Robotic Developmental Evolution

Evolution and development operate at different timescales; generations f...

0 Fabien C. Y. Benureau, et al. ∙

research

∙ 06/29/2020

Towards hybrid primary intersubjectivity: a neural robotics library for human science

Human-robot interaction is becoming an interesting area of research in c...

0 Hendry F. Chame, et al. ∙

research

∙ 05/27/2020

Goal-Directed Planning for Habituated Agents by Active Inference Using a Variational Recurrent Neural Network

It is crucial to ask how agents can achieve goals by generating action p...

0 Takazumi Matsumoto, et al. ∙

research

∙ 02/05/2020

Investigation of Multimodal and Agential Interactions in Human-Robot Imitation, based on frameworks of Predictive Coding and Active Inference

This study proposes a model for multimodal, imitative interaction of age...

0 Wataru Ohata, et al. ∙

research

∙ 12/23/2019

Variational Recurrent Models for Solving Partially Observable Control Tasks

In partially observable (PO) environments, deep reinforcement learning (...

19 Dongqi Han, et al. ∙

research

∙ 11/05/2019

Cognitive and motor compliance in intentional human-robot interaction

Embodiment and subjective experience in human-robot interaction are impo...

0 Hendry Ferreira Chame, et al. ∙

research

∙ 04/05/2019

A Neurorobotics Approach to Investigating the Emergence of Communication in Robots

This paper introduces our approach to building a robot with communicatio...

0 Jungsik Hwang, et al. ∙

research

∙ 03/12/2019

Goal-Directed Behavior under Variational Predictive Coding: Dynamic Organization of Visual Attention and Working Memory

Mental simulation is a critical cognitive function for goal-directed beh...

0 Minju Jung, et al. ∙

research

∙ 01/29/2019

Emergence of Hierarchy via Reinforcement Learning Using a Multiple Timescale Stochastic RNN

Although recurrent neural networks (RNNs) for reinforcement learning (RL...

12 Dongqi Han, et al. ∙

research

∙ 11/04/2018

Learning to Embed Probabilistic Structures Between Deterministic Chaos and Random Process in a Variational Bayes Predictive-Coding RNN

This study introduces a stochastic predictive-coding RNN model that can ...

0 Ahmadreza Ahmadi, et al. ∙

research

∙ 05/28/2018

Lifelong Learning of Spatiotemporal Representations with Dual-Memory Recurrent Self-Organization

Humans excel at continually acquiring and fine-tuning knowledge over sus...

0 German I. Parisi, et al. ∙

research

∙ 05/15/2018

A Dynamic Neural Network Approach to Generating Robot's Novel Actions: A Simulation Experiment

In this study, we investigate how a robot can generate novel and creativ...

0 Jungsik Hwang, et al. ∙

research

∙ 03/07/2018

Generating goal-directed visuomotor plans based on learning using a predictive coding type deep visuomotor recurrent neural network model

The current paper presents how a predictive coding type deep recurrent n...

0 Minkyu Choi, et al. ∙

research

∙ 08/02/2017

Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model

The current paper proposes a novel predictive coding type neural network...

0 Minkyu Choi, et al. ∙

research

∙ 06/30/2017

Bridging the Gap between Probabilistic and Deterministic Models: A Simulation Study on a Variational Bayes Predictive Coding Recurrent Neural Network Model

The current paper proposes a novel variational Bayes predictive coding R...

0 Ahmadreza Ahmadi, et al. ∙

research

∙ 06/08/2017

Predictive Coding-based Deep Dynamic Neural Network for Visuomotor Learning

This study presents a dynamic neural network model based on the predicti...

0 Jungsik Hwang, et al. ∙

research

∙ 06/08/2017

Seamless Integration and Coordination of Cognitive Skills in Humanoid Robots: A Deep Learning Approach

This study investigates how adequate coordination among the different co...

0 Jungsik Hwang, et al. ∙

research

∙ 05/24/2017

Adaptive Detrending to Accelerate Convolutional Gated Recurrent Unit Training for Contextual Video Recognition

Based on the progress of image recognition, video recognition has been e...

0 Minju Jung, et al. ∙

research

∙ 06/06/2016

Predictive Coding for Dynamic Vision : Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model

The current paper presents a novel recurrent neural network model, the p...

0 Minkyu Choi, et al. ∙

research

∙ 05/11/2016

Sensorimotor Input as a Language Generalisation Tool: A Neurorobotics Model for Generation and Generalisation of Noun-Verb Combinations with Sensorimotor Inputs

The paper presents a neurorobotics cognitive model to explain the unders...

0 Junpei Zhong, et al. ∙

research

∙ 02/05/2016

Recognition of Visually Perceived Compositional Human Actions by Multiple Spatio-Temporal Scales Recurrent Neural Networks

The current paper proposes a novel neural network model for recognizing ...

0 Haanvid Lee, et al. ∙

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