If we have a mind, then why do we make so many mistakes? The answer to this question lies in quantum physics.
Psychologists have long studied why people do not always make the right choices, even when they are aware of the consequences of their decisions. In theory, each of us is capable of rational choice, but think about how often you or your acquaintances have made knowingly wrong decisions. So why is it that none of us are perfect?
The answer is quite simple: it is about uncertainty. However, this is not just confusion or another human emotion, but the very uncertainty that underlies quantum mechanics. A paradigm called quantum reinforcement learning (QRL) is based on methods used in psychology and artificial intelligence development, and it stands in contrast to classical reinforcement learning (CRL).
The essence of classical reinforcement learning is simple: it involves a system of rewards and punishments. It does not matter whether you are teaching a child or a robot — successful actions should be rewarded, and failures should be punished.
As for the question of foolish decisions, the idea is that we make them based on the anticipated reward, but do not take into account the possible punishment. For example, you are waxing the floors, dreaming of how they will shine and how you will be praised, but in an hour or two you are taking your mother-in-law to the emergency room with a fracture and listening to her detailed account.
Thus, people make decisions considering the uncertainty inherent in the quantum universe, often without realizing it. This approach is often referred to as “maybe,” when it is impossible to predict the outcome of an event at the quantum level accurately, but hope for the best prevails.
Consequently, human cognition has a quantum nature, and the only way to explain human memory, cognition, and consciousness becomes quantum mechanics.
