Optimism Bias

Optimism bias, the tendency to overestimate the likelihood of positive outcomes, is a significant challenge across diverse fields, impacting decision-making in areas like reinforcement learning and game theory. Current research focuses on mitigating this bias through algorithmic approaches, such as incorporating pessimism or uncertainty estimates into models like actor-critic methods and multi-armed bandits, and by strategically revealing information in cooperative games to calibrate expectations. Addressing optimism bias is crucial for improving the reliability and safety of AI systems, particularly in applications like autonomous driving and resource allocation, where overly optimistic predictions can have severe consequences.