BRIDGING THE GENERALIZATION GAP IN VISUAL REINFORCEMENT LEARNING: A THEORETICAL AND EMPIRICAL STUDY

Alejandro Gómez; Fatima Al-Khalifa

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BRIDGING THE GENERALIZATION GAP IN VISUAL REINFORCEMENT LEARNING: A THEORETICAL AND EMPIRICAL STUDY

Alejandro Gómez ¹ , Fatima Al-Khalifa ²

¹ Department of Computer Science, Universidad de Buenos Aires, Argentina

² Department of Computer Engineering, King Saud University, Saudi Arabia

Issue Vol. 1 No. 01 (2024): Volume 01 Issue 01 --- Section Articles --- Published Date: 2024-12-09

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Abstract

Visual Reinforcement Learning (VRL) agents frequently suffer from a significant "generalization gap," exhibiting degraded performance when deployed in environments that subtly differ from their training conditions. This paper provides a comprehensive analysis of the factors contributing to this discrepancy, integrating theoretical insights with empirical evidence. We categorize and discuss various strategies employed to bridge this gap, including the pivotal roles of data augmentation, advanced representation learning techniques (such as self-supervised and invariant learning), regularization methods, domain randomization for sim-to-real transfer, and the integration of auxiliary tasks and structured policy approaches. Our findings underscore the importance of learning robust, invariant visual representations and the efficacy of exposing agents to diverse, augmented experiences. We highlight the ongoing challenges, particularly in quantifying and optimizing for true environmental invariance, and propose future research directions aimed at developing more adaptable and generalizable VRL systems capable of thriving in varied real-world scenarios.

Keywords

Reinforcement Learning, Visual Reinforcement Learning, Generalization, Data Augmentation

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BRIDGING THE GENERALIZATION GAP IN VISUAL REINFORCEMENT LEARNING: A THEORETICAL AND EMPIRICAL STUDY. (2024). European Journal of Emerging Artificial Intelligence, 1(01), 17-36. https://parthenonfrontiers.com/index.php/ejeai/article/view/46

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BRIDGING THE GENERALIZATION GAP IN VISUAL REINFORCEMENT LEARNING: A THEORETICAL AND EMPIRICAL STUDY

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