77 citations · 219 across the 30 of their papers we have counts for
7 papers · 1 filter
Addressing Optimism Bias in Sequence Modeling for Reinforcement Learning
Adam Villaflor, Zhe Huang, Swapnil Pande +2
Impressive results in natural language processing (NLP) based on the Transformer neural network architecture have inspired researchers to explore viewing offline reinforcement lear…
BATS: Best Action Trajectory Stitching
Ian Char, Viraj Mehta, Adam Villaflor +2
The problem of offline reinforcement learning focuses on learning a good policy from a log of environment interactions. Past efforts for developing algorithms in this area have rev…
Learning to Robustly Negotiate Bi-Directional Lane Usage in High-Conflict Driving Scenarios
Christoph Killing, Adam Villaflor, John M. Dolan
Recently, autonomous driving has made substantial progress in addressing the most common traffic scenarios like intersection navigation and lane changing. However, most of these su…
Measuring Similarity of Interactive Driving Behaviors Using Matrix Profile
Qin Lin, Wenshuo Wang, Yihuan Zhang +1
Understanding multi-vehicle interactive behaviors with temporal sequential observations is crucial for autonomous vehicles to make appropriate decisions in an uncertain traffic env…
Multi-Robot Informative Path Planning for Active Sensing of Environmental Phenomena: A Tale of Two Algorithms
Nannan Cao, Kian Hsiang Low, John M. Dolan
A key problem of robotic environmental sensing and monitoring is that of active sensing: How can a team of robots plan the most informative observation paths to minimize the uncert…
Decentralized Data Fusion and Active Sensing with Mobile Sensors for Modeling and Predicting Spatiotemporal Traffic Phenomena
Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan +4
The problem of modeling and predicting spatiotemporal traffic phenomena over an urban road network is important to many traffic applications such as detecting and forecasting conge…