Multi Agent Prediction

Multi-agent prediction focuses on forecasting the future behavior of multiple interacting agents, a crucial task in domains like autonomous driving and sports analytics. Current research emphasizes developing models that accurately capture complex interactions between agents, employing architectures such as graph neural networks, transformers, and attention mechanisms to achieve this. These advancements are improving the accuracy and efficiency of predictions, leading to safer autonomous systems and more insightful analyses of complex dynamic systems. The ultimate goal is to create robust and reliable prediction models that can handle the inherent uncertainties and complexities of multi-agent scenarios.