Papers › Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning

Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning

25 Oct 2021NeurIPS 2021 12arXiv:2110.12985archive 2025-07-28

Kibeom Kim, Min Whoo Lee, Yoonsung Kim, Je-Hwan Ryu, Minsu Lee, Byoung-Tak Zhang

Learning in a multi-target environment without prior knowledge about the targets requires a large amount of samples and makes generalization difficult. To solve this problem, it is important to be able to discriminate targets through semantic understanding. In this paper, we propose goal-aware cross-entropy (GACE) loss, that can be utilized in a self-supervised way using auto-labeled goal states alongside reinforcement learning. Based on the loss, we then devise goal-discriminative attention networks (GDAN) which utilize the goal-relevant information to focus on the given instruction. We evaluate the proposed methods on visual navigation and robot arm manipulation tasks with multi-target environments and show that GDAN outperforms the state-of-the-art methods in terms of task success ratio, sample efficiency, and generalization. Additionally, qualitative analyses demonstrate that our proposed method can help the agent become aware of and focus on the given instruction clearly, promoting goal-directed behavior.

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Actor_Critic kibeomkim/gace-gdan/GACE_GDAN/models.py official repository ran MIT (permissive) · b25b0b4bdba58c8f · report
Feature_Extractor kibeomkim/gace-gdan/GACE_GDAN/models.py official repository ran MIT (permissive) · 486178b159d9a858 · report
GDAN kibeomkim/gace-gdan/GACE_GDAN/models.py official repository ran MIT (permissive) · 2eb8379568cea70d · report
Goal_discriminator kibeomkim/gace-gdan/GACE_GDAN/models.py official repository ran MIT (permissive) · e3410ab0605200d8 · report
postprocess kibeomKim/GACE-GDAN/GACE_GDAN/agent.py official repository ran · our draft was wrong fingerprinted MIT (permissive) · 5f451cdfc6e5e92b · report
preprocess kibeomKim/GACE-GDAN/GACE_GDAN/agent.py official repository unverified MIT (permissive) · c579940fb7d7687f · report

Tasks

Reinforcement LearningReinforcement Learning (RL)Visual Navigationreinforcement-learning

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