  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.
