activity
20182021
most citedSymbol Emergence as an Interpersonal Multimodal Categorization

2 citations · 5 across the 3 of their papers we have counts for

collaborators

6 papers

cs.AI20211 cited

Multiagent Multimodal Categorization for Symbol Emergence: Emergent Communication via Interpersonal Cross-modal Inference

Yoshinobu Hagiwara, Kazuma Furukawa, Akira Taniguchi +1

This paper describes a computational model of multiagent multimodal categorization that realizes emergent communication. We clarify whether the computational model can reproduce th…

cs.RO20212 cited

Hierarchical Bayesian Model for the Transfer of Knowledge on Spatial Concepts based on Multimodal Information

Yoshinobu Hagiwara, Keishiro Taguchi, Satoshi Ishibushi +2

This paper proposes a hierarchical Bayesian model based on spatial concepts that enables a robot to transfer the knowledge of places from experienced environments to a new environm…

cs.RO2020

Spatial Concept-Based Navigation with Human Speech Instructions via Probabilistic Inference on Bayesian Generative Model

Akira Taniguchi, Yoshinobu Hagiwara, Tadahiro Taniguchi +1

Robots are required to not only learn spatial concepts autonomously but also utilize such knowledge for various tasks in a domestic environment. Spatial concept represents a multim…

cs.RO2020

Autonomous Planning Based on Spatial Concepts to Tidy Up Home Environments with Service Robots

Akira Taniguchi, Shota Isobe, Lotfi El Hafi +2

Tidy-up tasks by service robots in home environments are challenging in robotics applications because they involve various interactions with the environment. In particular, robots…

cs.CL20192 cited

Symbol Emergence as an Interpersonal Multimodal Categorization

Yoshinobu Hagiwara, Hiroyoshi Kobayashi, Akira Taniguchi +1

This study focuses on category formation for individual agents and the dynamics of symbol emergence in a multi-agent system through semiotic communication. Semiotic communication i…

cs.RO2018

Improved and Scalable Online Learning of Spatial Concepts and Language Models with Mapping

Akira Taniguchi, Yoshinobu Hagiwara, Tadahiro Taniguchi +1

We propose a novel online learning algorithm, called SpCoSLAM 2.0, for spatial concepts and lexical acquisition with high accuracy and scalability. Previously, we proposed SpCoSLAM…