14 citations · 18 across the 12 of their papers we have counts for
4 papers · 1 filter
Reinforcement Learning with Iterative Reasoning for Merging in Dense Traffic
Maxime Bouton, Alireza Nakhaei, David Isele +2
Maneuvering in dense traffic is a challenging task for autonomous vehicles because it requires reasoning about the stochastic behaviors of many other participants. In addition, the…
Interaction-Aware Multi-Agent Reinforcement Learning for Mobile Agents with Individual Goals
Anahita Mohseni-Kabir, David Isele, Kikuo Fujimura
In a multi-agent setting, the optimal policy of a single agent is largely dependent on the behavior of other agents. We investigate the problem of multi-agent reinforcement learnin…
Interactive Decision Making for Autonomous Vehicles in Dense Traffic
David Isele
Dense urban traffic environments can produce situations where accurate prediction and dynamic models are insufficient for successful autonomous vehicle motion planning. We investig…
Selective Experience Replay for Lifelong Learning
David Isele, Akansel Cosgun
Deep reinforcement learning has emerged as a powerful tool for a variety of learning tasks, however deep nets typically exhibit forgetting when learning multiple tasks in sequence.…