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Intuitive RL: Intro to Advantage-Actor-Critic (A2C)
Manage episode 411341528 series 3474148
This story was originally published on HackerNoon at: https://hackernoon.com/intuitive-rl-intro-to-advantage-actor-critic-a2c-4ff545978752.
Reinforcement learning (RL) practitioners have produced a number of excellent tutorials. Most, however, describe RL in terms of mathematical equations and abstract diagrams. We like to think of the field from a different perspective. RL itself is inspired by how animals learn, so why not translate the underlying RL machinery back into the natural phenomena they’re designed to mimic? Humans learn best through stories.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #machine-learning, #reinforcement-learning, #neural-networks, #deep-learning, #advantage-actor-critic, #hackernoon-es, and more.
This story was written by: @rudygilman. Learn more about this writer by checking @rudygilman's about page, and for more stories, please visit hackernoon.com.
212 episódios
Manage episode 411341528 series 3474148
This story was originally published on HackerNoon at: https://hackernoon.com/intuitive-rl-intro-to-advantage-actor-critic-a2c-4ff545978752.
Reinforcement learning (RL) practitioners have produced a number of excellent tutorials. Most, however, describe RL in terms of mathematical equations and abstract diagrams. We like to think of the field from a different perspective. RL itself is inspired by how animals learn, so why not translate the underlying RL machinery back into the natural phenomena they’re designed to mimic? Humans learn best through stories.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #machine-learning, #reinforcement-learning, #neural-networks, #deep-learning, #advantage-actor-critic, #hackernoon-es, and more.
This story was written by: @rudygilman. Learn more about this writer by checking @rudygilman's about page, and for more stories, please visit hackernoon.com.
212 episódios
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