5 citations · 10 across the 4 of their papers we have counts for
4 papers
Soft Actor-Critic with Inhibitory Networks for Faster Retraining
Jaime S. Ide, Daria Mićović, Michael J. Guarino +3
Reusing previously trained models is critical in deep reinforcement learning to speed up training of new agents. However, it is unclear how to acquire new skills when objectives an…
Multi-Object Tracking with Deep Learning Ensemble for Unmanned Aerial System Applications
Wanlin Xie, Jaime Ide, Daniel Izadi +7
Multi-object tracking (MOT) is a crucial component of situational awareness in military defense applications. With the growing use of unmanned aerial systems (UASs), MOT methods fo…
Hierarchical Reinforcement Learning for Air Combat at DARPA's AlphaDogfight Trials
Adrian P. Pope, Jaime S. Ide, Daria Micovic +7
Autonomous control in high-dimensional, continuous state spaces is a persistent and important challenge in the fields of robotics and artificial intelligence. Because of high risk…
Propositional and Relational Bayesian Networks Associated with Imprecise and Qualitative Probabilistic Assesments
Fabio Gagliardi Cozman, Cassio Polpo de Campos, Jaime Ide +1
This paper investigates a representation language with flexibility inspired by probabilistic logic and compactness inspired by relational Bayesian networks. The goal is to handle p…