Net Present Value
Net Present Value (NPV) calculations, central to decision-making across various fields, aim to quantify the value of future benefits and costs in today's terms. Current research emphasizes improving NPV estimations by incorporating uncertainty, particularly through advanced algorithms like those based on Partially Observable Markov Decision Processes (POMDPs) and incorporating machine learning techniques to better model complex, dynamic systems and account for changing market conditions. This refined understanding of NPV has significant implications for resource allocation in areas such as finance, healthcare, and environmental management, leading to more informed and efficient decision-making.
Papers
Tango*: Constrained synthesis planning using chemically informed value functions
Daniel Armstrong, Zlatko Joncev, Jeff Guo, Philippe Schwaller
The Use of Artificial Intelligence in Military Intelligence: An Experimental Investigation of Added Value in the Analysis Process
Christian Nitzl, Achim Cyran, Sascha Krstanovic, Uwe M. Borghoff
Value Imprint: A Technique for Auditing the Human Values Embedded in RLHF Datasets
Ike Obi, Rohan Pant, Srishti Shekhar Agrawal, Maham Ghazanfar, Aaron Basiletti
Value-Spectrum: Quantifying Preferences of Vision-Language Models via Value Decomposition in Social Media Contexts
Jingxuan Li, Yuning Yang, Shengqi Yang, Linfan Zhang, Ying Nian Wu