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Entropy (Basel, Switzerland)|December 8, 2020
Goal-Directed Planning for Habituated Agents by Active Inference Using a Variational Recurrent Neural NetworkTakazumi Matsumoto, Jun TaniEntropy (Basel, Switzerland)|November 24, 2023
Incremental Learning of Goal-Directed Actions in a Dynamic Environment by a Robot Using Active InferenceTakazumi Matsumoto, Wataru Ohata, Jun TaniFrontiers in Computational Neuroscience|July 17, 2025
Modeling autonomous shifts between focus state and mind-wandering using a predictive-coding-inspired variational recurrent neural networkHenrique Oyama, Takazumi Matsumoto, Jun TaniEntropy (Basel, Switzerland)|August 28, 2025
Active Inference with Dynamic Planning and Information Gain in Continuous Space by Inferring Low-Dimensional Latent StatesTakazumi Matsumoto, Kentaro Fujii, Shingo Murata, et al.Neural Computation|August 19, 2021
Emergence of Content-Agnostic Information Processing by a Robot Using Active Inference, Visual Attention, Working Memory, and PlanningJeffrey Frederic Queiẞer, Minju Jung, Takazumi Matsumoto, et al.Entropy (Basel, Switzerland)|April 23, 2022
Goal-Directed Planning and Goal Understanding by Extended Active Inference: Evaluation through Simulated and Physical Robot ExperimentsTakazumi Matsumoto, Wataru Ohata, Fabien C Y Benureau, et al.Neural Networks : the Official Journal of the International Neural Network Society|February 11, 2003
Learning to generate articulated behavior through the bottom-up and the top-down interaction processesJun TaniFrontiers in Neurorobotics|October 30, 2008
On the interactions between top-down anticipation and bottom-up regressionJun TaniNeural Computation|September 17, 2019
A Novel Predictive-Coding-Inspired Variational RNN Model for Online Prediction and RecognitionAhmadreza Ahmadi, Jun TaniPlos Computational Biology|November 8, 2008
Emergence of functional hierarchy in a multiple timescale neural network model: a humanoid robot experimentYuichi Yamashita, Jun TaniPageof 6