Deep Causal Learning for Robotic Intelligence

by   Yangming Li, et al.

This invited review discusses causal learning in the context of robotic intelligence. The paper introduced the psychological findings on causal learning in human cognition, then it introduced the traditional statistical solutions on causal discovery and causal inference. The paper reviewed recent deep causal learning algorithms with a focus on their architectures and the benefits of using deep nets and discussed the gap between deep causal learning and the needs of robotic intelligence.


page 9

page 10

page 11


Causal inference in drug discovery and development

To discover new drugs is to seek and to prove causality. As an emerging ...

Deep Causal Learning: Representation, Discovery and Inference

Causal learning has attracted much attention in recent years because cau...

Beauty Learning and Counterfactual Inference

This work showcases a new approach for causal discovery by leveraging us...

Robotic Supervised Autonomy: A Review

This invited paper discusses a new but important problem, supervised aut...

Numerical Analysis of the Causal Action Principle in Low Dimensions

The numerical analysis of causal fermion systems is advanced by employin...

The tropical geometry of causal inference for extremes

Extreme value statistics is the max analogue of classical statistics, wh...

Please sign up or login with your details

Forgot password? Click here to reset