We introduce a novel experimental paradigm where participants explore multiple learning activities, some easy, others difficult. However, the LPH has not been extensively studied using behavioral experimentation.This thesis provides an empirical examination of the LPH. The Learning Progress Hypothesis (LPH) is attractive, not only because it is consistent with several studies of human curiosity, but also because it resonates with existing theories on metacognitive self-regulation in learning. Due to similar computational challenges facing artificial and biological learners, researchers have proposed that progress-based intrinsic motivation might have evolved in humans to help us transition from babies with few skills and little knowledge to knowledgeable grownups capable of performing many sophisticated tasks. In artificial learners, progressbased intrinsic motivation enables autonomous exploration of the environment (including the agent’s own body), resulting in better performance, more efficient learning, and richer skill sets. The Learning Progress Hypothesis (LPH) proposes that humans are motivated by feelings of and/or beliefs about progress in knowledge (including progress in competence). But where does intrinsic motivation to learn and seek information come from? Today, with the thriving synergy between perpetually advancing fields of psychology, neuroscience, and computer science, we are well positioned to investigate this question. We have come to understand, in the context of learning and discovery, that intrinsic motivation (namely, intrinsically motivated information-seeking) is foundational for the biological and technological success of our species. Since then, research on intrinsic motivation has been steadily gaining momentum. Intrinsic motivation – the desire to do things for their inherent joy and pleasure – has received its first share of scientific attention over 70years ago, ever since we saw monkeys solving puzzles for free. In contrast, when the agent made little progress on the problem before suddenly solving it, it experiences high RPE.

When the agent solved the problem gradually, it experiences little RPE. (C) Graph plotting the reward prediction error experienced by the two agents upon completion of the problem.

Right panel: Here, the agent estimates that the problem will take a very long time to complete and is inaccurate about the actual time to solve the problem. Here, the completion level doesn't increase for a considerable period of time and the problem is solved suddenly. (B) Left panel: Sequence of data provided to the model.

Here, the agent's completion time estimate is near to the true completion time. Right panel: Agent's completion time estimate as it observes the data sequence in the left panel. Here, the completion level increments steadily and the problem is solved gradually. (A) Left panel: Sequence of data provided to the model. Solving a problem suddenly results in an Aha! moment. These results highlight the importance of metacognitive prediction errors and deepen our understanding of human metareasoning. We provide support to our theory across three large-scale pre-registered experiments on problem solving, demonstrating a link between metacognitive prediction errors and Aha! moments. We posit that this metacognitive error is analogous to a positive reward prediction error thereby explaining why we feel so good after an Aha! moment. when we solve a problem much faster than we expected to solve it. Aha! moments arise when we experience a positive error in this metacognitive prediction, i.e. Our theory posits that during problem-solving, in addition to solving the problem, people also maintain a metacognitive model of their ability to solve the problem as well as a prediction about the time it would take them to solve that problem. In this work, we present a theoretical framework that explains why we experience Aha! moments. Psychologists have long been fascinated with understanding the nature of Aha! moments, moments when we transition from not knowing to suddenly realizing the solution to a problem.

That aha moment