Chapter
Comparing Evolutionary Computation and Deep Learning
54:11 - 1:00:37 (06:26)
The use of population-based methods in evolutionary computation can be more effective than deep learning in certain contexts when trying to explore and discover new solutions. However, deep learning is still valuable in individual learning during their lifetime.
Clips
The effectiveness of evolutionary computation versus deep learning methods depends on the type of task being performed.
54:11 - 56:09 (01:58)
Summary
The effectiveness of evolutionary computation versus deep learning methods depends on the type of task being performed. While deep learning may excel in certain contexts, evolutionary computation may be more effective in others, such as decision making and practical applications like healthcare and stock market investment.
ChapterComparing Evolutionary Computation and Deep Learning
Episode#177 – Risto Miikkulainen: Neuroevolution and Evolutionary Computation
PodcastLex Fridman Podcast
This podcast explores the difference between population-based and individual-based learning methods such as reinforcement learning in creating engineering solutions using the example of simulated robot walking.
56:09 - 1:00:37 (04:28)
Summary
This podcast explores the difference between population-based and individual-based learning methods such as reinforcement learning in creating engineering solutions using the example of simulated robot walking.