Probabilistic Information

Probabilistic information focuses on representing and reasoning with uncertainty, moving beyond deterministic predictions to quantify the likelihood of different outcomes. Current research emphasizes developing methods for generating and utilizing probabilistic information in diverse applications, including trajectory prediction (using models like composite probabilistic Bézier curves), misinformation detection (via probabilistic Markovian models), and improving human decision-making by incorporating AI uncertainty quantification. This work is significant because it enhances the reliability and robustness of AI systems and improves the quality of decisions made under uncertainty across various fields, from social media analysis to complex multi-target decision problems.