The Evolution theory of Learning: From Natural Selection to Reinforcement Learning
It addresses the problem of bridging biological evolution and artificial intelligence for researchers in both fields, but appears incremental as it reviews existing connections.
This paper explores the connections between evolution and reinforcement learning, suggesting that reinforcement learning principles can enhance understanding of evolution and feedback in evolutionary systems.
Evolution is a fundamental process that shapes the biological world we inhabit, and reinforcement learning is a powerful tool used in artificial intelligence to develop intelligent agents that learn from their environment. In recent years, researchers have explored the connections between these two seemingly distinct fields, and have found compelling evidence that they are more closely related than previously thought. This paper examines these connections and their implications, highlighting the potential for reinforcement learning principles to enhance our understanding of evolution and the role of feedback in evolutionary systems.