Nonparametric Bayesian Word Discovery for Symbol Emergence in RoboticsTadahiro Taniguchi
This is a material for invited talk in the workshop on Machine Learning Methods for High-
Level Cognitive Capabilities in Robotics 2016 (ML-HLCR2016) held in IROS2016, Korea.
First part shows several methods to sample points from arbitrary distributions. Second part shows application to population genetics to infer population size and divergence time using obtained sequence data.
This is a slide for the invited talk at The 4th Workshop on Naturalistic Driving Data Analytics,
IEEE IV2017, Los Angeles, 11th June, 2017.
This talk summarizes a series of work on a symbolization approach toward naturalistic driving behavior data.
Most of the works are conducted by collaboration between DESNO co. and Ritsumeikan university
Symbol Emergence in Robotics: Language Acquisition via Real-world Sensorimoto...Tadahiro Taniguchi
Invited talk at Gatsby-Kakenhi Joint Workshop on AI and Neuroscience, London, 12th May, 2017
This talk is delivered as a part of the session about artificial general intelligence.
Symbol emergence in robotics can be regarded as a research activity contributing to develop an AGI.