This paper proposes a generative probabilistic model integrating emergen...
We present a computational model for a symbol emergence system that enab...
In this study, we explore the emergence of symbols during interactions
b...
In the studies on symbol emergence and emergent communication in a popul...
Autonomous robots are required to actively and adaptively learn the
cate...
The human brain, among its several functions, analyzes the double
articu...
In this study, we propose a head-to-head type (H2H-type) inter-personal
...
Emergent communication, also known as symbol emergence, seeks to investi...
Navigating to destinations using human speech instructions is an importa...
Human infants acquire their verbal lexicon from minimal prior knowledge ...
This paper describes a computational model of multiagent multimodal
cate...
Preserving the linguistic content of input speech is essential during vo...
This paper proposes methods for unsupervised lexical acquisition for rel...
Using the spatial structure of various indoor environments as prior
know...
Building a humanlike integrative artificial cognitive system, that is, a...
We constructed a hippocampal formation (HPF)-inspired probabilistic
gene...
This paper proposes a hierarchical Bayesian model based on spatial conce...
Robots are required to not only learn spatial concepts autonomously but ...
Tidy-up tasks by service robots in home environments are challenging in ...
This paper describes a framework for the development of an integrative
c...
This study focuses on category formation for individual agents and the
d...
In this paper, we propose a novel online learning algorithm, SpCoSLAM 2....
In this paper, we propose an online learning algorithm based on a
Rao-Bl...
In this paper, we propose a novel unsupervised learning method for the
l...