# Symbol Emergence as Inter-personal Categorization with Head-to-head Latent Word

arXiv: https://arxiv.org/abs/2205.15027 · HTML: https://mlsanity.com/paper/2205.15027/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 31 references that are in the map.
- First posted on arXiv 24 May 2022.

## Builds on (most cited first, 11 of 11)

- [Learning Attentional Communication for Multi-Agent Cooperation](https://mlsanity.com/paper/1805.07733/) (2018)
- [Emergent Multi-Agent Communication in the Deep Learning Era](https://mlsanity.com/paper/2006.02419/) (2020)
- [Ease-of-Teaching and Language Structure from Emergent Communication](https://mlsanity.com/paper/1906.02403/) (2019)
- [Biases for Emergent Communication in Multi-agent Reinforcement Learning](https://mlsanity.com/paper/1912.05676/) (2019)
- [Symbol Emergence in Robotics: A Survey](https://mlsanity.com/paper/1509.08973/) (2015)
- [Neuro-SERKET: Development of Integrative Cognitive System through the Composition of Deep Probabilistic Generative Models](https://mlsanity.com/paper/1910.08918/) (2019)
- [SERKET: An Architecture for Connecting Stochastic Models to Realize a Large-Scale Cognitive Model](https://mlsanity.com/paper/1712.00929/) (2017)
- [Symbol Emergence as an Interpersonal Multimodal Categorization](https://mlsanity.com/paper/1905.13443/) (2019)
- [Predictive Processing in Cognitive Robotics: a Review](https://mlsanity.com/paper/2101.06611/) (2021)
- [Multiagent Multimodal Categorization for Symbol Emergence: Emergent Communication via Interpersonal Cross-modal Inference](https://mlsanity.com/paper/2109.07194/) (2021)
- [Emergent Communication with World Models](https://mlsanity.com/paper/2002.09604/) (2020)

## Built on by (most cited first, 2 of 2)

- [System 0/1/2/3: Quad-process theory for multi-timescale embodied collective cognitive systems](https://mlsanity.com/paper/2503.06138/) (2025)
- [Symbol emergence as interpersonal cross-situational learning: the emergence of lexical knowledge with combinatoriality](https://mlsanity.com/paper/2306.15837/) (2023)

## Abstract (arXiv)

In this study, we propose a head-to-head type (H2H-type) inter-personal multimodal Dirichlet mixture (Inter-MDM) by modifying the original Inter-MDM, which is a probabilistic generative model that represents the symbol emergence between two agents as multiagent multimodal categorization. A Metropolis--Hastings method-based naming game based on the Inter-MDM enables two agents to collaboratively perform multimodal categorization and share signs with a solid mathematical foundation of convergence. However, the conventional Inter-MDM presumes a tail-to-tail connection across a latent word variable, causing inflexibility of the further extension of Inter-MDM for modeling a more complex symbol emergence. Therefore, we propose herein a head-to-head type (H2H-type) Inter-MDM that treats a latent word variable as a child node of an internal variable of each agent in the same way as many prior studies of multimodal categorization. On the basis of the H2H-type Inter-MDM, we propose a naming game in the same way as the conventional Inter-MDM. The experimental results show that the H2H-type Inter-MDM yields almost the same performance as the conventional Inter-MDM from the viewpoint of multimodal categorization and sign sharing.