2024 Poster "sample efficiency" Papers

24 papers found

Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment

Chen Zhang, Qiang HE, Yuan Zhou et al.

ICML 2024posterarXiv:2406.01103

A Unified Linear Programming Framework for Offline Reward Learning from Human Demonstrations and Feedback

Kihyun Kim, Jiawei Zhang, Asuman Ozdaglar et al.

ICML 2024posterarXiv:2405.12421

Better & Faster Large Language Models via Multi-token Prediction

Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Roziere et al.

ICML 2024posterarXiv:2404.19737

Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation

Michelle Pan, Mariah Schrum, Vivek Myers et al.

ICML 2024posterarXiv:2406.06714

Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming

Hany Hamed, Subin Kim, Dongyeong Kim et al.

ICML 2024poster

Feasible Reachable Policy Iteration

Shentao Qin, Yujie Yang, Yao Mu et al.

ICML 2024poster

Hieros: Hierarchical Imagination on Structured State Space Sequence World Models

Paul Mattes, Rainer Schlosser, Ralf Herbrich

ICML 2024poster

How Does Goal Relabeling Improve Sample Efficiency?

Sirui Zheng, Chenjia Bai, Zhuoran Yang et al.

ICML 2024poster

Learning to Play Atari in a World of Tokens

Pranav Agarwal, Sheldon Andrews, Samira Ebrahimi Kahou

ICML 2024posterarXiv:2406.01361

LLM-Empowered State Representation for Reinforcement Learning

Boyuan Wang, Yun Qu, Yuhang Jiang et al.

ICML 2024poster

Model-based Reinforcement Learning for Parameterized Action Spaces

Renhao Zhang, Haotian Fu, Yilin Miao et al.

ICML 2024posterarXiv:2404.03037

Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL

Yu Luo, Tianying Ji, Fuchun Sun et al.

ICML 2024posterarXiv:2405.18520

Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning

Michal Nauman, Michał Bortkiewicz, Piotr Milos et al.

ICML 2024posterarXiv:2403.00514

Quality-Diversity with Limited Resources

Ren-Jian Wang, Ke Xue, Cong Guan et al.

ICML 2024posterarXiv:2406.03731

Reflective Policy Optimization

Yaozhong Gan, yan renye, zhe wu et al.

ICML 2024posterarXiv:2406.03678

Reinforcement Learning within Tree Search for Fast Macro Placement

Zijie Geng, Jie Wang, Ziyan Liu et al.

ICML 2024poster

Reward Shaping for Reinforcement Learning with An Assistant Reward Agent

Haozhe Ma, Kuankuan Sima, Thanh Vinh Vo et al.

ICML 2024poster

Rich-Observation Reinforcement Learning with Continuous Latent Dynamics

Yuda Song, Lili Wu, Dylan Foster et al.

ICML 2024posterarXiv:2405.19269

Sample-Efficient Multiagent Reinforcement Learning with Reset Replay

Yaodong Yang, Guangyong Chen, Jianye Hao et al.

ICML 2024poster

SAPG: Split and Aggregate Policy Gradients

Jayesh Singla, Ananye Agarwal, Deepak Pathak

ICML 2024posterarXiv:2407.20230

Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic

Tianying Ji, Yu Luo, Fuchun Sun et al.

ICML 2024poster

SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning

Matthias Weissenbacher, Rishabh Agarwal, Yoshinobu Kawahara

ICML 2024poster

Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization

Hyeonah Kim, Minsu Kim, Sungsoo Ahn et al.

ICML 2024posterarXiv:2306.01276

Uncertainty-Aware Reward-Free Exploration with General Function Approximation

Junkai Zhang, Weitong Zhang, Dongruo Zhou et al.

ICML 2024posterarXiv:2406.16255