# How Can Robots Trust Each Other For Better Cooperation? A Relative Needs Entropy Based Robot-Robot Trust Assessment Model

arXiv: https://arxiv.org/abs/2105.07443 · HTML: https://mlsanity.com/paper/2105.07443/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 22 references that are in the map.
- First posted on arXiv 16 May 2021.

## Builds on (most cited first, 3 of 3)

- [Modeling Trust in Human-Robot Interaction: A Survey](https://mlsanity.com/paper/2011.04796/) (2020)
- [Hierarchical Needs Based Self-Adaptive Framework For Cooperative Multi-Robot System](https://mlsanity.com/paper/2004.10920/) (2020)
- [Needs-driven Heterogeneous Multi-Robot Cooperation in Rescue Missions](https://mlsanity.com/paper/2009.00288/) (2020)

## Built on by (most cited first, 9 of 9)

- [A Hierarchical Game-Theoretic Decision-Making for Cooperative Multi-Agent Systems Under the Presence of Adversarial Agents](https://mlsanity.com/paper/2303.16641/) (2023)
- [Utility Theory based Cognitive Modeling in the Application of Robotics: A Survey](https://mlsanity.com/paper/2306.09445/) (2023)
- [Object-Oriented Material Classification and 3D Clustering for Improved Semantic Perception and Mapping in Mobile Robots](https://mlsanity.com/paper/2407.06077/) (2024)
- [Bayesian Soft Actor-Critic: A Directed Acyclic Strategy Graph Based Deep Reinforcement Learning](https://mlsanity.com/paper/2208.06033/) (2022)
- [Hierarchical Needs-driven Agent Learning Systems: From Deep Reinforcement Learning To Diverse Strategies](https://mlsanity.com/paper/2302.13132/) (2023)
- [A Strategy-Oriented Bayesian Soft Actor-Critic Model](https://mlsanity.com/paper/2303.04193/) (2023)
- [GHQ: Grouped Hybrid Q Learning for Heterogeneous Cooperative Multi-agent Reinforcement Learning](https://mlsanity.com/paper/2303.01070/) (2023)
- [Communication-Efficient Reinforcement Learning in Swarm Robotic Networks for Maze Exploration](https://mlsanity.com/paper/2305.17087/) (2023)
- [Edge Computing based Human-Robot Cognitive Fusion: A Medical Case Study in the Autism Spectrum Disorder Therapy](https://mlsanity.com/paper/2401.00776/) (2024)

## Abstract (arXiv)

Cooperation in multi-agent and multi-robot systems can help agents build various formations, shapes, and patterns presenting corresponding functions and purposes adapting to different situations. Relationships between agents such as their spatial proximity and functional similarities could play a crucial role in cooperation between agents. Trust level between agents is an essential factor in evaluating their relationships' reliability and stability, much as people do. This paper proposes a new model called Relative Needs Entropy (RNE) to assess trust between robotic agents. RNE measures the distance of needs distribution between individual agents or groups of agents. To exemplify its utility, we implement and demonstrate our trust model through experiments simulating a heterogeneous multi-robot grouping task in a persistent urban search and rescue mission consisting of tasks at two levels of difficulty. The results suggest that RNE trust-Based grouping of robots can achieve better performance and adaptability for diverse task execution compared to the state-of-the-art energy-based or distance-based grouping models.