activity
20182022
most citedA Survey of Deep Reinforcement Learning in Video Games

149 citations · 237 across the 16 of their papers we have counts for

collaborators

23 papers

cs.LG2022

Prototypical context-aware dynamics generalization for high-dimensional model-based reinforcement learning

Junjie Wang, Yao Mu, Dong Li +6

The latent world model provides a promising way to learn policies in a compact latent space for tasks with high-dimensional observations, however, its generalization across diverse…

cs.RO20223 cited

Conditional Goal-oriented Trajectory Prediction for Interacting Vehicles with Vectorized Representation

Ding Li, Qichao Zhang, Shuai Lu +2

This paper aims to tackle the interactive behavior prediction task, and proposes a novel Conditional Goal-oriented Trajectory Prediction (CGTP) framework to jointly generate scene-…

cs.RO2022

TrajGen: Generating Realistic and Diverse Trajectories with Reactive and Feasible Agent Behaviors for Autonomous Driving

Qichao Zhang, Yinfeng Gao, Yikang Zhang +5

Realistic and diverse simulation scenarios with reactive and feasible agent behaviors can be used for validation and verification of self-driving system performance without relying…

cs.MA202252 cited

UNMAS: Multi-Agent Reinforcement Learning for Unshaped Cooperative Scenarios

Jiajun Chai, Weifan Li, Yuanheng Zhu +4

Multi-agent reinforcement learning methods such as VDN, QMIX, and QTRAN that adopt centralized training with decentralized execution (CTDE) framework have shown promising results i…

cs.RO2022

Multi-task Safe Reinforcement Learning for Navigating Intersections in Dense Traffic

Yuqi Liu, Qichao Zhang, Dongbin Zhao

Multi-task intersection navigation including the unprotected turning left, turning right, and going straight in dense traffic is still a challenging task for autonomous driving. Fo…

cs.GT20214 cited

Empirical Policy Optimization for -Player Markov Games

Yuanheng Zhu, Dongbin Zhao, Mengchen Zhao +1

In single-agent Markov decision processes, an agent can optimize its policy based on the interaction with environment. In multi-player Markov games (MGs), however, the interaction…