Explore prediction and planning under uncertainty in this comprehensive lecture by Alfredo Canziani. Delve into topics such as Model Predictive Control, Stochastic Environment, RGB Representation, and Lane Cost. Learn about practical applications and gain insights into Word Models, Problem-solving approaches, Inference techniques, and Agent behavior. Discover how to navigate complex decision-making scenarios in uncertain environments through this informative 1-hour 15-minute presentation, which is part of a broader course on deep learning and its applications.
Overview
Syllabus
Introduction
Model Predictive Control
Stochastic Environment
RGB Representation
Lane Cost
In Practice
Outline
Word Model
Problem
Inference
Agent
Taught by
Alfredo Canziani
