Prospect Theory

Cumulative Prospect Theory (CPT) refines expected utility theory by incorporating psychological factors like loss aversion and probability weighting into decision-making models, better reflecting human choices under risk and uncertainty. Current research focuses on integrating CPT into reinforcement learning algorithms, developing methods for automatically identifying and explaining risk-seeking preferences in organizational settings, and applying CPT to diverse domains such as inventory management, multi-agent systems, and human-AI interaction. This work has significant implications for improving the design of AI systems, enhancing organizational decision-making, and advancing our understanding of human behavior in complex environments.