Future Reasoning
Future reasoning research explores how artificial intelligence systems can predict, plan, and understand temporal dynamics. Current efforts concentrate on improving the accuracy and efficiency of AI-driven forecasting across diverse domains, from weather prediction using large meteorological models and graph neural networks to financial market analysis and even generating synthetic data for training other models. This field is crucial for advancing AI capabilities in areas like autonomous systems, personalized medicine, and risk management, ultimately impacting both scientific understanding and real-world applications.
Papers
Boosting Studies of Multi-Agent Reinforcement Learning on Google Research Football Environment: the Past, Present, and Future
Yan Song, He Jiang, Haifeng Zhang, Zheng Tian, Weinan Zhang, Jun Wang
From Text to Trends: A Unique Garden Analytics Perspective on the Future of Modern Agriculture
Parag Saxena
Implementation of The Future of Drug Discovery: QuantumBased Machine Learning Simulation (QMLS)
Yifan Zhou, Yan Shing Liang, Yew Kee Wong, Haichuan Qiu, Yu Xi Wu, Bin He
An Outlook into the Future of Egocentric Vision
Chiara Plizzari, Gabriele Goletto, Antonino Furnari, Siddhant Bansal, Francesco Ragusa, Giovanni Maria Farinella, Dima Damen, Tatiana Tommasi