# Reinforcement Learning in Robotics

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/reinforcement-learning-in-robotics/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers encompasses a wide range of advancements in reinforcement learning algorithms and their applications, including deep learning, neural networks, robotics, autonomous control, policy gradient methods, multi-agent systems, model-based learning, curiosity-driven exploration, and simulation to real-world transfer. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t10462 |
| Works | 51 |

## Topic papers all

Showing 15 of 51.

- [On Learning, Representing, and Generalizing a Task in a Humanoid Robot](https://scholariq.org/papers/on-learning-representing-and-generalizing-a-task-in-a-humanoid-robot/)
- [Dynamic Task Prioritization for Multitask Learning](https://scholariq.org/papers/dynamic-task-prioritization-for-multitask-learning/)
- [Optimization of global production scheduling with deep reinforcement learning](https://scholariq.org/papers/optimization-of-global-production-scheduling-with-deep-reinforcement-learning/)
- [A Survey of Robot Learning Strategies for Human-Robot Collaboration in Industrial Settings](https://scholariq.org/papers/a-survey-of-robot-learning-strategies-for-human-robot-collaboration-in/)
- [Learning from Humans](https://scholariq.org/papers/learning-from-humans/)
- [Q-Learning for robust satisfaction of signal temporal logic specifications](https://scholariq.org/papers/q-learning-for-robust-satisfaction-of-signal-temporal-logic-specifications/)
- [A Deep Reinforcement Learning Framework Based on an Attention Mechanism and Disjunctive Graph Embedding for the Job-Shop Scheduling Problem](https://scholariq.org/papers/a-deep-reinforcement-learning-framework-based-on-an-attention-mechanism-and/)
- [Comprehensive Ocean Information-Enabled AUV Path Planning Via Reinforcement Learning](https://scholariq.org/papers/comprehensive-ocean-information-enabled-auv-path-planning-via-reinforcement/)
- [Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration<sup>0</sup>](https://scholariq.org/papers/open-x-embodiment-robotic-learning-datasets-and-rt-x-models-open-x-embodiment/)
- [Deep reinforcement learning for semiconductor production scheduling](https://scholariq.org/papers/deep-reinforcement-learning-for-semiconductor-production-scheduling/)
- [DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset](https://scholariq.org/papers/droid-a-large-scale-in-the-wild-robot-manipulation-dataset/)
- [Collaborative Robot-Assisted Endovascular Catheterization with Generative Adversarial Imitation Learning](https://scholariq.org/papers/collaborative-robot-assisted-endovascular-catheterization-with-generative/)
- [ChatGPT Empowered Long-Step Robot Control in Various Environments: A Case Application](https://scholariq.org/papers/chatgpt-empowered-long-step-robot-control-in-various-environments-a-case/)
- [A game-theoretic model and best-response learning method for ad hoc coordination in multiagent systems](https://scholariq.org/papers/a-game-theoretic-model-and-best-response-learning-method-for-ad-hoc-coordination/)
- [Entropy, optimization and counting](https://scholariq.org/papers/entropy-optimization-and-counting/)

## Topic primary papers

- [Collaborative Robot-Assisted Endovascular Catheterization with Generative Adversarial Imitation Learning](https://scholariq.org/papers/collaborative-robot-assisted-endovascular-catheterization-with-generative/)
- [A game-theoretic model and best-response learning method for ad hoc coordination in multiagent systems](https://scholariq.org/papers/a-game-theoretic-model-and-best-response-learning-method-for-ad-hoc-coordination/)
- [Human, I wrote a song for you: An experiment testing the influence of machines’ attributes on the AI-composed music evaluation](https://scholariq.org/papers/human-i-wrote-a-song-for-you-an-experiment-testing-the-influence-of-machines/)
- [First Order Constrained Optimization in Policy Space](https://scholariq.org/papers/first-order-constrained-optimization-in-policy-space/)
- [Playing 20 Question Game with Policy-Based Reinforcement Learning](https://scholariq.org/papers/playing-20-question-game-with-policy-based-reinforcement-learning/)
- [Sampling Based Approaches for Minimizing Regret in Uncertain Markov Decision Processes (MDPs)](https://scholariq.org/papers/sampling-based-approaches-for-minimizing-regret-in-uncertain-markov-decision/)
- [A Critical Investigation of Deep Reinforcement Learning for Navigation](https://scholariq.org/papers/a-critical-investigation-of-deep-reinforcement-learning-for-navigation/)
- [Cooperative Assistance in Robotic Surgery through Multi-Agent Reinforcement Learning](https://scholariq.org/papers/cooperative-assistance-in-robotic-surgery-through-multi-agent-reinforcement/)
- [Learning robotic ultrasound scanning using probabilistic temporal ranking.](https://scholariq.org/papers/learning-robotic-ultrasound-scanning-using-probabilistic-temporal-ranking/)
- [Social decision-making in a large-scale MultiAgent system considering the influence of empathy](https://scholariq.org/papers/social-decision-making-in-a-large-scale-multiagent-system-considering-the/)
- [CASRL: Collision Avoidance with Spiking Reinforcement Learning Among Dynamic, Decision-Making Agents](https://scholariq.org/papers/casrl-collision-avoidance-with-spiking-reinforcement-learning-among-dynamic/)
- [HypRL: Reinforcement Learning of Control Policies for Hyperproperties](https://scholariq.org/papers/hyprl-reinforcement-learning-of-control-policies-for-hyperproperties/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.