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Reward Shaping with Subgoals for Social Navigation
Social navigation has been gaining attentions with the growth in machine...
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Towards Deployment of Deep-Reinforcement-Learning-Based Obstacle Avoidance into Conventional Autonomous Navigation Systems
Recently, mobile robots have become important tools in various industrie...
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Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments
In this paper we consider the problem of robot navigation in simple maze...
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From Crystallized Adaptivity to Fluid Adaptivity in Deep Reinforcement Learning -- Insights from Biological Systems on Adaptive Flexibility
Recent developments in machine-learning algorithms have led to impressiv...
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Teaching a Machine to Read Maps with Deep Reinforcement Learning
The ability to use a 2D map to navigate a complex 3D environment is quit...
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Lifelong Federated Reinforcement Learning: A Learning Architecture for Navigation in Cloud Robotic Systems
This paper was motivated by the problem of how to make robots fuse and t...
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Relational Graph Learning for Crowd Navigation
We present a relational graph learning approach for robotic crowd naviga...
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Analysis of Social Robotic Navigation approaches: CNN Encoder and Incremental Learning as an alternative to Deep Reinforcement Learning
Dealing with social tasks in robotic scenarios is difficult, as having humans in the learning loop is incompatible with most of the state-of-the-art machine learning algorithms. This is the case when exploring Incremental learning models, in particular the ones involving reinforcement learning. In this work, we discuss this problem and possible solutions by analysing a previous study on adaptive convolutional encoders for a social navigation task.
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