"deep reinforcement learning" Papers
36 papers found
Conference
Agent-Aware Training for Agent-Agnostic Action Advising in Deep Reinforcement Learning
Yaoquan Wei, Shunyu Liu, Jie Song et al.
APIRL: Deep Reinforcement Learning for REST API Fuzzing
Myles Foley, Sergio Maffeis
Contrastive Representation for Interactive Recommendation
Jingyu Li, Zhiyong Feng, Dongxiao He et al.
Estimating cognitive biases with attention-aware inverse planning
Sounak Banerjee, Daphne Cornelisse, Deepak Gopinath et al.
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization
Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh et al.
Logic-Q: Improving Deep Reinforcement Learning-based Quantitative Trading via Program Sketch-based Tuning
Zhiming Li, Junzhe Jiang, Yushi Cao et al.
Measure gradients, not activations! Enhancing neuronal activity in deep reinforcement learning
Jiashun Liu, Zihao Wu, Johan Obando Ceron et al.
Mind the GAP! The Challenges of Scale in Pixel-based Deep Reinforcement Learning
Ghada Sokar, Pablo Samuel Castro
Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning
Guozheng Ma, Lu Li, Zilin Wang et al.
RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviors
Fengshuo Bai, Runze Liu, Yali Du et al.
Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics
Lorenzo Magnino, Kai Shao, Zida Wu et al.
Solving hidden monotone variational inequalities with surrogate losses
Ryan D'Orazio, Danilo Vucetic, Zichu Liu et al.
SonoGym: High Performance Simulation for Challenging Surgical Tasks with Robotic Ultrasound
Yunke Ao, Masoud Moghani, Mayank Mittal et al.
Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning
Roger Creus Castanyer, Johan Obando Ceron, Lu Li et al.
Time Reversal Symmetry for Efficient Robotic Manipulations in Deep Reinforcement Learning
Yunpeng Jiang, Jianshu Hu, Paul Weng et al.
ULTHO: Ultra-Lightweight yet Efficient Hyperparameter Optimization in Deep Reinforcement Learning
Mingqi Yuan, Bo Li, Xin Jin et al.
Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment
Chen Zhang, Qiang HE, Yuan Zhou et al.
Analyzing Generalization in Policy Networks: A Case Study with the Double-Integrator System
Ruining Zhang, Haoran Han, Maolong Lv et al.
Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents
Chung-En Sun, Sicun Gao, Lily Weng
Contextual Pre-planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning
Guy Azran, Mohamad H Danesh, Stefano Albrecht et al.
Discerning Temporal Difference Learning
Jianfei Ma
Distributional Bellman Operators over Mean Embeddings
Li Kevin Wenliang, Gregoire Deletang, Matthew Aitchison et al.
DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems
Kaibo He, Chenhui Zuo, Chengtian Ma et al.
Fractional Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing
Lyudong Jin, Ming Tang, Meng Zhang et al.
Graph-Based Prediction and Planning Policy Network (GP3Net) for Scalable Self-Driving in Dynamic Environments Using Deep Reinforcement Learning
Jayabrata Chowdhury, Venkataramanan Shivaraman, Suresh Sundaram et al.
In value-based deep reinforcement learning, a pruned network is a good network
Johan Obando Ceron, Aaron Courville, Pablo Samuel Castro
INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer
Han Fang, Zhihao Song, Paul Weng et al.
Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning
Arvi Jonnarth, Jie Zhao, Michael Felsberg
Learning the Target Network in Function Space
Kavosh Asadi, Yao Liu, Shoham Sabach et al.
SHINE: Shielding Backdoors in Deep Reinforcement Learning
Zhuowen Yuan, Wenbo Guo, Jinyuan Jia et al.
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
Jesse Farebrother, Jordi Orbay, Quan Vuong et al.
Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization
Hyeonah Kim, Minsu Kim, Sungsoo Ahn et al.
Task Planning for Object Rearrangement in Multi-Room Environments
Karan Mirakhor, Sourav Ghosh, Dipanjan Das et al.
Understanding and Diagnosing Deep Reinforcement Learning
Ezgi Korkmaz
Unlock the Cognitive Generalization of Deep Reinforcement Learning via Granular Ball Representation
Jiashun Liu, Jianye Hao, Yi Ma et al.
Why Do Animals Need Shaping? A Theory of Task Composition and Curriculum Learning
Jin Hwa Lee, Stefano Mannelli, Andrew Saxe