2018FY「Beyond Deep Learning: Towards the Fusion with Symbolic Reasoning (2)」

Semantic Understanding and Imagination [JP]

Prof. Yutaka Matsuo discusses the potential of artificial intelligence that connects symbolic reasoning and deep learning.

Mar 5, 2019

Taming Learned Representations [JP]

From the viewpoint of “representation engineering,” Dr. Hiroshi Yamakawa discusses how to handle representations acquired by intelligent systems through learning.

Mar 5, 2019

Coevolution of Natural Intelligence and Artificial Intelligence: Towards the “Creation of Knowledge” [JP]

This lecture focuses on the method of fusing pattern information processing, which is the strong point of deep learning, and symbolic reasoning.

Mar 5, 2019

Fusion of Probabilistic Generative Model and Deep Learning in the Field of Symbol Emergence in Robotics [JP]

How do intelligent systems generate symbols? This lecture introduces you to the research field of symbol emergence in robotics and features the future direction of its fusion with deep learning.

Mar 5, 2019

Cognition and Behavioral Change Based on Predictive Uncertainty: From the Perspective of Neurorobotics [JP]

How will deep learning based on neural network change robots? Prof. Tetsuya Ogata introduces you to the research on cognitive developmental robotics.

Mar 5, 2019

Towards the Next Generation Artificial Intelligence: Fusion of Autonomy and Sociality Through the Emergence and Development Based on Embodiment [JP]

This lecture focuses on measures to avoid “pitfalls” of deep learning that hinder the social implementation of AI.

Mar 5, 2019

Hierarchy of Intelligence [JP]

Taking the position that higher-order reasoning is essential to intelligence, Dr. Hideyuki Nakashima presents an architecture that combines deep learning (bottom-up) and symbol processing (top-down).

Mar 5, 2019