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Learning Reward Functions by Integrating Human Demonstrations and Preferences
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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APRIL: Active Preference Learning-Based Reinforcement Learning
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Preference-based reinforcement learning: a formal framework and a policy iteration algorithm
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A survey of robot learning from demonstration
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Bayesian Inverse Reinforcement Learning
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Individual choice behavior: A theoretical analysis.
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Active Reward Learning from Critiques
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MuJoCo: A physics engine for model-based control
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Apprenticeship learning via inverse reinforcement learning
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Bayesian inference for Plackett-Luce ranking models
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Do You Want Your Autonomous Car To Drive Like You?
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Data-Driven Motion Mappings Improve Transparency in Teleoperation
inferredcites →https://doi.org/10.1177/0278364915581193openalex-snapshot
Learning preferences for manipulation tasks from online coactive feedback
inferredcites →https://doi.org/10.1184/r1/6550949openalex-snapshot
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
inferredcites →https://doi.org/10.1184/r1/6555512openalex-snapshot
Maximum Entropy Inverse Reinforcement Learning
inferredcites →https://doi.org/10.1198/016214507000001049openalex-snapshot
Exploring Voting Blocs Within the Irish Electorate
inferredcites →https://doi.org/10.15607/rss.2012.viii.010openalex-snapshot
Formalizing Assistive Teleoperation
inferredcites →https://doi.org/10.15607/rss.2015.xi.032openalex-snapshot
Shared Autonomy via Hindsight Optimization
inferredcites →https://doi.org/10.15607/rss.2017.xiii.053openalex-snapshot
Active Preference-Based Learning of Reward Functions
inferredcites →https://doi.org/10.1561/9781601984616openalex-snapshot
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
inferredcites →https://doi.org/10.21437/interspeech.2012-72openalex-snapshot
Preference-learning based inverse reinforcement learning for dialog control
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Diagnosing Non-Intermittent Anomalies in Reinforcement Learning Policy Executions (Short Paper)
inferredcites →https://doi.org/10.48550/arxiv.1011.0108openalex-snapshot
An Active Learning Algorithm for Ranking from Pairwise Preferences with an Almost Optimal Query Complexity
inferredcites →https://doi.org/10.48550/arxiv.1603.00448openalex-snapshot
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization
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Generative Adversarial Imitation Learning
inferredcites →https://doi.org/10.48550/arxiv.1811.06521openalex-snapshot
Reward learning from human preferences and demonstrations in Atari
inferredcites →https://doi.org/10.48550/arxiv.1901.02161openalex-snapshot
Risk-Aware Active Inverse Reinforcement Learning
inferredcites →https://doi.org/10.5555/2031678.2031705openalex-snapshot
Integrating reinforcement learning with human demonstrations of varying ability
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Robots That Can Anticipate and Learn in Human-Robot Teams
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Learning Reward Functions from a Combination of Demonstration and Evaluative Feedback
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APReL: A Library for Active Preference-based Reward Learning Algorithms
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Similarity-Aware Skill Reproduction based on Multi-Representational Learning from Demonstration
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Fast Adaptation of Deep Reinforcement Learning-Based Navigation Skills to Human Preference
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Aligning Human Preferences with Baseline Objectives in Reinforcement Learning
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Data-Efficient Learning from Human Interventions for Mobile Robots
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Toward Grounded Commonsense Reasoning
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Genetic Imitation Learning by Reward Extrapolation
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Active Learning of Reward Dynamics from Hierarchical Queries
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Game-Theoretic Planning for Risk-Aware Interactive Agents
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Active Preference Learning using Maximum Regret
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Task Decoupling in Preference-based Reinforcement Learning for Personalized Human-Robot Interaction
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Pairwise Preferences-Based Optimization of a Path-Based Velocity Planner in Robotic Sealing Tasks
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Interactive Reward Tuning: Interactive Visualization for Preference Elicitation
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The Impact of VR and 2D Interfaces on Human Feedback in Preference-Based Robot Learning
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Test-Driven Inverse Reinforcement Learning Using Scenario-Based Testing
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Pairwise Preferences-Based Optimization of a Path-Based Velocity Planner in Robotic Sealing Tasks
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Autonomous UAV Navigation in Complex Environments using Human Feedback
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How Much Progress Did I Make? An Unexplored Human Feedback Signal for Teaching Robots
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Unobstructed Programming-by-Demonstration for Force-Based Assembly Utilizing External Force-Torque Sensors
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Understanding the Relationship between Interactions and Outcomes in Human-in-the-Loop Machine Learning
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Explanation-Guided Reward Alignment
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A survey of decision-making and planning methods for self-driving vehicles
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Combining exploration and imitation in contact-rich task learning on an articulated soft robot arm
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Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations
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Asking Easy Questions: A User-Friendly Approach to Active Reward Learning
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When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans
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Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
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Active Preference-Based Gaussian Process Regression for Reward Learning
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Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks
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Learning Reward Functions from Scale Feedback
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Enhancing Control in Chemical Processes using Reinforcement from Human Feedback
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