mlsanityData to 7 Oct 2026

A General, Evolution-Inspired Reward Function for Social Robotics

arXiv 2202.00617 ↗First posted 1 Feb 2022cs.RO cs.LGcited by 0

On the map: Offline RL and imitation learning from data → Social robot navigation

Abstract (arXiv)

The field of social robotics will likely need to depart from a paradigm of designed behaviours and imitation learning and adopt modern reinforcement learning (RL) methods to enable robots to interact fluidly and efficaciously with humans. In this paper, we present the Social Reward Function as a mechanism to provide (1) a real-time, dense reward function necessary for the deployment of RL agents in social robotics, and (2) a standardised objective metric for comparing the efficacy of different social robots. The Social Reward Function is designed to closely mimic those genetically endowed social perception capabilities of humans in an effort to provide a simple, stable and culture-agnostic reward function. Presently, datasets used in social robotics are either small or significantly out-of-domain with respect to social robotics. The use of the Social Reward Function will allow larger in-domain datasets to be collected close to the behaviour policy of social robots, which will allow both further improvements to reward functions and to the behaviour policies of social robots. We believe this will be the key enabler to developing efficacious social robots in the future.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Social robot navigation, one of 13 directions in Offline RL and imitation learning from data. Builds on 21 of its 49 references that are in the map. First posted on arXiv 1 Feb 2022.

Builds on

21 of 49 references.

References · 21

  1. 2017The Kinetics Human Action Video Datasetcited by 1,894
  2. 2020Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problemscited by 1,873
  3. 2016OpenAI Gymcited by 1,684
  4. 2018World Modelscited by 1,444
  5. 2020D4RL: Datasets for Deep Data-Driven Reinforcement Learningcited by 1,406
  6. 2019NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understandingcited by 530
  7. 2017Robust Adversarial Reinforcement Learningcited by 439
  8. 2013Challenges in Representation Learning: A report on three machine learning contestscited by 301
  9. 2021Unsolved Problems in ML Safetycited by 291
  10. 2019RoboNet: Large-Scale Multi-Robot Learningcited by 268
  11. 2019Adversarial Policies: Attacking Deep Reinforcement Learningcited by 209
  12. 2018RoboTurk: A Crowdsourcing Platform for Robotic Skill Learning through Imitationcited by 202
9 more
  1. 2021How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learnedcited by 201
  2. 2019End-to-End Robotic Reinforcement Learning without Reward Engineeringcited by 115
  3. 2019Degenerate Feedback Loops in Recommender Systemscited by 67
  4. 2017CycleGAN, a Master of Steganographycited by 63
  5. 2021On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learningcited by 59
  6. 2019Is Deep Reinforcement Learning Really Superhuman on Atari? Leveling the playing fieldcited by 14
  7. 2020AIR-Act2Act: Human-human interaction dataset for teaching non-verbal social behaviors to robotscited by 9
  8. 2017Robot gains Social Intelligence through Multimodal Deep Reinforcement Learningcited by 7
  9. 2019Multimodal Speech Emotion Recognition and Ambiguity Resolutioncited by 4

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  1. 2023REBEL: Reward Regularization-Based Approach for Robotic Reinforcement Learning from Human Feedback
  2. 2022Feedback-efficient Active Preference Learning for Socially Aware Robot Navigation
  3. 2024REvolve: Reward Evolution with Large Language Models using Human Feedback
  4. 2025RoboScape-R: Unified Reward-Observation World Models for Generalizable Robotics Training via RL
  5. 2023Effect of Adapting to Human Preferences on Trust in Human-Robot Teaming ↗
  6. 2026SPLC: Social Preference Learning for Crowd Robot Navigation
  7. 2025Towards an Adaptive Social Game-Playing Robot: An Offline Reinforcement Learning-Based Framework
  8. 2025Reward Evolution with Graph-of-Thoughts: A Bi-Level Language Model Framework for Reinforcement Learning