MaartenGr/ReinLife
Creating Artificial Life with Reinforcement Learning
This project offers a unique way to simulate artificial life where digital organisms learn behaviors like survival, hunting, and reproduction throughout their lifespan, rather than through generations. Using reinforcement learning, individual entities are rewarded for beneficial actions and punished for poor ones. Scientists or researchers in artificial life and complex systems would use this to model individual-level learning and emergent behaviors in simulated ecosystems.
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Use this if you want to explore how individual entities in a simulated environment can learn complex survival and reproductive strategies during their 'lifetime' using reinforcement learning.
Not ideal if you primarily focus on genetic evolution across many generations as the main driver of behavioral change in artificial life simulations.
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84
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14
Language
Python
License
MIT
Category
Last pushed
May 03, 2024
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