Just like how animals learn to adapt to different environments, scientists have developed a model that allows monkeys to learn a complex target search task. This task involves the agent gazing at one of four light spots, with two neighboring spots alternating as the correct target. The model uses a dynamic state space and a ‘history-in-episode architecture’ to make decisions based on past actions and results. In comparison to the conventional SARSA method, the model with the dynamic state space performed much better and achieved close to the theoretical optimum. This breakthrough in reinforcement learning paves the way for highly adaptable learning systems in complex environments. To dive deeper into this fascinating research, check out the full article!
Dr. David Lowemann
Dr. David Lowemann, M.Sc, Ph.D., is a co-founder of the Institute for the Future of Human Potential, where he leads the charge in pioneering Self-Enhancement Science for the Success of Society. With a keen interest in exploring the untapped potential of the human mind, Dr. Lowemann has dedicated his career to pushing the boundaries of human capabilities and understanding.Armed with a Master of Science degree and a Ph.D. in his field, Dr. Lowemann has consistently been at the forefront of research and innovation, delving into ways to optimize human performance, cognition, and overall well-being. His work at the Institute revolves around a profound commitment to harnessing cutting-edge science and technology to help individuals lead more fulfilling and intelligent lives.Dr. Lowemann's influence extends to the educational platform BetterSmarter.me, where he shares his insights, findings, and personal development strategies with a broader audience. His ongoing mission is shaping the way we perceive and leverage the vast capacities of the human mind, offering invaluable contributions to society's overall success and collective well-being.