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Tag Archives: Deep Learning

Correct Me if I am Wrong: Interactive Learning for Robotic Manipulation

Deep reinforcement learning is successfully applied in many real-world robotic tasks. However, it is limited to domains in which a simulator is available or environments that have been tailored and instrumented for the agent’s training. Interactive learning approach is useful in training not just industrial robotic systems. Image credit: Auledas via Wikimedia, CC-BY-SA-4.0 Therefore, a recent paper proposes an interactive ...

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Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning

Deep reinforcement learning (DRL) has been successfully used to solve robotics tasks like locomotion, manipulation, or navigation. However, complex tasks require a long training time. A recent paper on arXiv.org explores massive parallelism for the improvement of the quality and time-to-deployment of DRL policies. Robonaut. Image credit NASA via Pixabay The researchers examine how the standard RL formulation and the ...

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Focus on Impact: Indoor Exploration with Intrinsic Motivation

Robotic exploration is the task of autonomously navigating an unknown environment to gather sufficient information to represent it. Usually, deep reinforcement learning-based algorithms are employed, and extrinsic rewards based on occupancy anticipation are used in training. However, such rewards require knowledge about the precise layout of the training environments, which is expensive to gather. Therefore, a recent paper proposes to ...

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