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1
Introduction
2
Problem
3
Mathematics
4
Driving
5
Machine Learning History
6
Machine Learning Evolution
7
Core Features of Learning
8
The Gauntlet
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Modular Cognitive Structures
10
Incremental Learning
11
Prior Knowledge
12
Innate Knowledge
13
Why should we change paradigms
14
Are there any questions
15
What is cobweb
16
Learning
17
Prodigy
18
Sage
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What can we do
20
Questions
21
Critiques
Description:
Explore a thought-provoking seminar on developing AI systems that learn in a human-like manner. Delve into the challenge posed by Pat Langley from Stanford University, as he illustrates this concept using mathematics and driving domains. Examine the history of machine learning and its evolving relationship with cognitive psychology. Discover the characteristics of human behavior that form a 'computational gauntlet' for AI systems to overcome. Learn about five AI systems that have successfully navigated most of these obstacles, serving as role models for future research. Gain insights into encouraging more studies on human-like learning in AI. Understand the speaker's extensive background in AI and cognitive science, including his contributions to scientific knowledge discovery and experimental studies of machine learning.

The Computational Gauntlet of Human-Like Learning

USC Information Sciences Institute
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