# Survey of Design Paradigms for Social Robots

arXiv: https://arxiv.org/abs/2407.20556 · HTML: https://mlsanity.com/paper/2407.20556/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 20 of its 61 references that are in the map.
- First posted on arXiv 30 Jul 2024.

## Builds on (most cited first, 20 of 20)

- [Personalizing Dialogue Agents: I have a dog, do you have pets too?](https://mlsanity.com/paper/1801.07243/) (2018)
- [Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey](https://mlsanity.com/paper/2105.04387/) (2021)
- [Survey on Evaluation Methods for Dialogue Systems](https://mlsanity.com/paper/1905.04071/) (2019)
- [Task-Oriented Dialog Systems that Consider Multiple Appropriate Responses under the Same Context](https://mlsanity.com/paper/1911.10484/) (2019)
- [MoEL: Mixture of Empathetic Listeners](https://mlsanity.com/paper/1908.07687/) (2019)
- [A Comprehensive Assessment of Dialog Evaluation Metrics](https://mlsanity.com/paper/2106.03706/) (2021)
- [Proactive Human-Machine Conversation with Explicit Conversation Goals](https://mlsanity.com/paper/1906.05572/) (2019)
- [Towards Exploiting Background Knowledge for Building Conversation Systems](https://mlsanity.com/paper/1809.08205/) (2018)
- [Multimodal Dialogue Response Generation](https://mlsanity.com/paper/2110.08515/) (2021)
- [Hallucinations in Neural Automatic Speech Recognition: Identifying Errors and Hallucinatory Models](https://mlsanity.com/paper/2401.01572/) (2024)
- [Improving Knowledge-aware Dialogue Generation via Knowledge Base Question Answering](https://mlsanity.com/paper/1912.07491/) (2019)
- [Unsupervised Context Rewriting for Open Domain Conversation](https://mlsanity.com/paper/1910.08282/) (2019)
- [A Syntactically Constrained Bidirectional-Asynchronous Approach for Emotional Conversation Generation](https://mlsanity.com/paper/1806.07000/) (2018)
- [ERICA: An Empathetic Android Companion for Covid-19 Quarantine](https://mlsanity.com/paper/2106.02325/) (2021)
- [A Survey on Dialogue Management in Human-Robot Interaction](https://mlsanity.com/paper/2307.10897/) (2023)
- [Augmenting Knowledge through Statistical, Goal-oriented Human-Robot Dialog](https://mlsanity.com/paper/1907.03390/) (2019)
- [RMES: Real-Time Micro-Expression Spotting Using Phase From Riesz Pyramid](https://mlsanity.com/paper/2305.05523/) (2023)
- [Designing Loving-Kindness Meditation in Virtual Reality for Long-Distance Romantic Relationships](https://mlsanity.com/paper/2309.11816/) (2023)
- [Reducing Stress and Anxiety in the Metaverse: A Systematic Review of Meditation, Mindfulness and Virtual Reality](https://mlsanity.com/paper/2209.14645/) (2022)
- [ERIT Lightweight Multimodal Dataset for Elderly Emotion Recognition and Multimodal Fusion Evaluation](https://mlsanity.com/paper/2407.17772/) (2024)

## Built on by (most cited first, 1 of 1)

- [End-to-End Facial Expression Detection in Long Videos](https://mlsanity.com/paper/2504.07660/) (2025)

## Abstract (arXiv)

The demand for social robots in fields like healthcare, education, and entertainment increases due to their emotional adaptation features. These robots leverage multimodal communication, incorporating speech, facial expressions, and gestures to enhance user engagement and emotional support. The understanding of design paradigms of social robots is obstructed by the complexity of the system and the necessity to tune it to a specific task. This article provides a structured review of social robot design paradigms, categorizing them into cognitive architectures, role design models, linguistic models, communication flow, activity system models, and integrated design models. By breaking down the articles on social robot design and application based on these paradigms, we highlight the strengths and areas for improvement in current approaches. We further propose our original integrated design model that combines the most important aspects of the design of social robots. Our approach shows the importance of integrating operational, communicational, and emotional dimensions to create more adaptive and empathetic interactions between robots and humans.