51 citations · 307 across the 33 of their papers we have counts for
10 papers · 1 filter
Generative Emergent Communication: Large Language Model is a Collective World Model
Tadahiro Taniguchi, Ryo Ueda, Tomoaki Nakamura +2
Large Language Models (LLMs) have demonstrated a remarkable ability to capture extensive world knowledge, yet how this is achieved without direct sensorimotor experience remains a…
Control as Probabilistic Inference as an Emergent Communication Mechanism in Multi-Agent Reinforcement Learning
Tomoaki Nakamura, Akira Taniguchi, Tadahiro Taniguchi
This paper proposes a generative probabilistic model integrating emergent communication and multi-agent reinforcement learning. The agents plan their actions by probabilistic infer…
Emergent Communication through Metropolis-Hastings Naming Game with Deep Generative Models
Tadahiro Taniguchi, Yuto Yoshida, Akira Taniguchi +1
Constructive studies on symbol emergence systems seek to investigate computational models that can better explain human language evolution, the creation of symbol systems, and the…
Unsupervised Multimodal Word Discovery based on Double Articulation Analysis with Co-occurrence cues
Akira Taniguchi, Hiroaki Murakami, Ryo Ozaki +1
Human infants acquire their verbal lexicon with minimal prior knowledge of language based on the statistical properties of phonological distributions and the co-occurrence of other…
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…
Unsupervised Lexical Acquisition of Relative Spatial Concepts Using Spoken User Utterances
Rikunari Sagara, Ryo Taguchi, Akira Taniguchi +4
This paper proposes methods for unsupervised lexical acquisition for relative spatial concepts using spoken user utterances. A robot with a flexible spoken dialog system must be ab…
A Whole Brain Probabilistic Generative Model: Toward Realizing Cognitive Architectures for Developmental Robots
Tadahiro Taniguchi, Hiroshi Yamakawa, Takayuki Nagai +5
Building a humanlike integrative artificial cognitive system, that is, an artificial general intelligence (AGI), is the holy grail of the artificial intelligence (AI) field. Furthe…
Hippocampal formation-inspired probabilistic generative model
Akira Taniguchi, Ayako Fukawa, Hiroshi Yamakawa
In building artificial intelligence (AI) agents, referring to how brains function in real environments can accelerate development by reducing the design space. In this study, we pr…
Online Spatial Concept and Lexical Acquisition with Simultaneous Localization and Mapping
Akira Taniguchi, Yoshinobu Hagiwara, Tadahiro Taniguchi +1
In this paper, we propose an online learning algorithm based on a Rao-Blackwellized particle filter for spatial concept acquisition and mapping. We have proposed a nonparametric Ba…
Spatial Concept Acquisition for a Mobile Robot that Integrates Self-Localization and Unsupervised Word Discovery from Spoken Sentences
Akira Taniguchi, Tadahiro Taniguchi, Tetsunari Inamura
In this paper, we propose a novel unsupervised learning method for the lexical acquisition of words related to places visited by robots, from human continuous speech signals. We ad…