42:22

Open-ended and AI-generating Algorithms in the Era of Foundation Models: Research Talk by Jeff Clune

02:31:45

ICML 2019 Tutorial: Recent Advances in Population-Based Search for Deep Neural Networks

11:56

Deep Curiosity Search: Seaquest (Best)

02:32

Deep Curiosity Search: Seaquest

01:09

Deep Curiosity Search: Montezuma's Revenge (Best)

01:01

Deep Curiosity Search: Montezuma's Revenge

02:28

Robotics task main treatments after 15000 generations [Supplementary material]

02:44

Maze navigation task [Supplementary material]

02:31

Robotics task CMOEA and NSGA-II after 75000 generations [Supplementary material]

01:26

The artificial intelligence developed to identify and count wild animals

22:43

What is Deep Learning? How will it Change the World?

02:08

KUKA Greeting Robot - Automatic Facial Recognition via Deep Learning by a KUKA Robot

02:50

Aligning Phenotypic and Genotypic Modularity [Supplementary material]

01:24

PPGN: Sampling between 10 classes

02:30

Visualizations of output class neurons of CaffeNet throughout training - NIPS 2016

02:30

Visualizations of neurons at all 8 layers of CaffeNet throughout training - NIPS 2016

25:04

Talk: Robots that can adapt like animals

02:03

Evolving a Single Modular Robot Brain to Perform Six Different Tasks

25:16

Talk: Does aligning genotypic and phenotypic modularity improve the evolution of neural networks?

01:04:46

Deep Learning Overview & Visualizing What Deep Neural Networks Learn

05:25

Neural modularity helps organisms evolve to learn new skills without forgetting old skills

05:34

Deep Neural Networks are Easily Fooled

24:35

Talk summarizing Evolving Neural Networks That Are Both Modular and Regular

02:10

The Laramie Robotics Club

21:14

Talk summarizing Encouraging Creative Thinking in Robots...

19:18

Talk summarizing Novelty Search Creates Robots with General Skills for Exploration

05:10

Encouraging Creative Thinking in Robots: The Creative Thinking Approach

04:38

Automated Generation of Environments to Test the General Learning Capabilities of AI Agents

07:53

Novelty Search Creates Robots with General Skills for Exploration

05:06

Evolving Artificial Neural Networks That Are Both Modular and Regular

01:54

Overview of the Evolving Artificial Intelligence Lab at the University of Wyoming

23:59

Evolved Sensitive Periods in Learning

21:53

Costs and Benefits of Learning

03:26

Evolving Soft Robots with Multiple Materials (muscle, bone, etc.)

02:22

Why does modularity evolve? The evolutionary origins of modularity

57:54

Evolving artificial neural networks with generative encodings inspired by developmental biology

03:39

Multi-Objective Landscape Exploration (MOLE) algorithm. Explore all areas of your fitness landscape

03:19

Golem Project: Evolve virtual creatures and 3D print them to walk in the real world

00:31

Evolving Modular Networks: Video for "The Evolutionary Origins of Modularity"

01:40

Evolving Gaits for Physical Robots Directly in Hardware with the HyperNEAT Generative Encoding

02:31

Evolving Gaits for Legged Robots: Neural Networks with Geometric Patterns Perform Better

59:24

Evolving Regular, Modular Neural Networks

02:00

EndlessForms.com - Design objects with evolution and 3D print them!

05:00

EndlessForms.com - Design objects with evolution and 3D print them! (longer video)