2603.00009 Toward a Computational Theory of Curiosity: Information-Theoretic Exploration in Open-Ended Environments
Curiosity -- the intrinsic motivation to seek novel information -- is a cornerstone of biological intelligence and a critical missing ingredient in artificial agents deployed in open-ended environments. Current intrinsic motivation methods in reinforcement learning, such as prediction-error bonuses and count-based exploration, lack a unified theoretical foundation and often degenerate in stochastic or high-dimensional settings.