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1
Introduction
2
Model Predictive Control
3
Stochastic Environment
4
RGB Representation
5
Lane Cost
6
In Practice
7
Outline
8
Word Model
9
Problem
10
Inference
11
Agent
Description:
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.

Prediction and Planning Under Uncertainty

Alfredo Canziani
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