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Showing 1 to 3 of 3 for “"Adversarial Inverse Reinforcement Learning"”.
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Adversarial Inverse Reinforcement Learning with Noisy Observations
<p>Inverse reinforcement learning (IRL) has emerged as a popular approach for training robots from human/expert demonstration, where a learner/robot infers the expert's hidden reward function using the demonstrations and a simulator. We argue that noise is inevitable in certain parts of the …
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An Intent-based Neural Monte Carlo Tree Search Framework for Synthesis of Printed Circuit Boards
… datasets, culminating in a process called LFS (Learning Feedback System). This process allows using past data to accelerate MCTS with deep RL models on new or similar board configurations. Datasets are utilized with forms of dataset-based Reinforcement Learning (RL) algorithms, known as …
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Data-Driven Routing for Autonomous Trucks: Learning from Human Behavior with Context Awareness and Privacy Protection
… specifically on these data-driven and behavior-learning challenges, not on hardware or sensor-level issues. This work presents a unified framework for smart route planning for autonomous heavy-duty trucks and pursues three technical objectives: (i) accurate map matching under sparse GPS …