Recent papers
View all →Synchronizing Minds through Collective Predictive Coding: A Computational Model of Parent-Infant Homeostatic Co-Regulation
Yushi Tsubamoto, Takato Horii
Inter-brain synchrony (IBS) observed in real-time dyadic interactions, including parent--infant exchanges, suggests that two agents come to share aligned latent representations through interaction. Yet computational accounts of how such alignment can arise between agents that have only local sensory access and asymmetric internal knowledge remain underdeveloped. We propose a constructive model of parent--infant homeostatic co-regulation that integrates a POMDP formulation of active interoceptive inference with the Metropolis--Hastings Naming Game (MHNG) derived from the Collective Predictive Coding (CPC) hypothesis. In our model, the parent observes the infant only through an exteroceptive signal while the infant directly senses its own interoceptive state; the two agents agree on regulatory actions through a shared communicative variable whose acceptance is determined by a locally computable Metropolis--Hastings probability. The agents are further endowed with asymmetric generative-model knowledge: the parent knows how actions transform visceral states but must learn what the infant's body is communicating, whereas the infant perceives its visceral state directly but must learn how actions affect it. In a $6 \times 6$ visceral-state grid world, MHNG-mediated interaction regulated the infant's visceral state more adaptively than one-sided control conditions, and the two posteriors became rapidly aligned. Notably, this latent-state alignment emerged far earlier than the convergence of the learned generative matrices, indicating that representational synchrony does not presuppose fully shared world models. These results offer a minimal constructive account of latent-state alignment compatible with IBS reported in hyperscanning studies and support CPC as a candidate computational basis for inter-brain alignment.
Emergence of Social Reality of Emotion through a Social Allostasis Model with Dynamic Interpretants
Kentaro Nomura, Yushi Tsubamoto, Takato Horii
The theory of constructed emotion defines social reality as the community-level consensus on emotion concepts assigned to interoceptive sensations arising from bodily allostasis and social interaction. In this study, we simulate this emergence process using a computational model that integrates symbol emergence with degrees of freedom in symbol interpretation and active inference. Two agents receive interoceptive signals, exchange inferred symbols, and simultaneously adapt their bodily control goals and symbol interpretations to each other. Experimental results show that the interoceptive prior preferences and symbol probability distributions of the two agents converge, confirming the emergence of social reality grounded in social consensus.
Emergent Communication for Co-constructed Emotion Between Embodied Agents via Collective Predictive Coding
Zehang Zhang, Nguyen Le Hoang, Tadahiro Taniguchi, et al.
According to the theory of constructed emotion, the brain actively forms emotion categories by integrating multimodal bodily signals, and constructs emotional experiences by using these categories to predict and interpret sensory inputs. While research has advanced in modeling individual emotion construction, the social process of co-construction-how a shared understanding of emotions emerges between individuals-remains computationally underexplored. This study investigates this process by modeling emergent communication between two embodied agents using the Metropolis-Hastings Naming Game (MHNG), grounded in the Collective Predictive Coding (CPC) framework. Our experiments, using visual, auditory, and simulated interoceptive inputs, yield two main findings. First, MHNG-based communication significantly improves the alignment, clarity, and inter-agent agreement of the learned emotion categories compared to non-communicative and non-selective baselines, with the alignment effect concentrated at the symbolic layer rather than the perceptual latent representation. Second, even when the two agents have systematically divergent interoceptive dynamics, communication still produces robust categorical alignment, with distinct, category-specific reshaping patterns of each agent's emotion categories-consistent with the constructed-emotion view that interoceptive heterogeneity is constitutive of, rather than an obstacle to, shared emotional meaning. These findings provide computational support for the co-constructionist view of emotion and extend the CPC framework from physical to socially-grounded domains.
Recent articles
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記号創発スタディノート#7 言語/記号は人を使って世界を予測する～集合的予測符号化（CPC）仮説
こんにちは、記号創発アウトリーチチームです。本連載「記号創発スタディノート」は、京都大学の谷口忠大（通称：たにちゅー）教授を中心に10年以上にわたり展開されてきた「記号創発システム論」について、その可能性と意義、中心的な手法、今後の展望についてコンパクトに解説するシリーズです。◆これまでの回：・第1回：なぜ、いま記号創発システム論なのか？ ～生成AI時代の「意味」の新学理・第2回：記号創発システム論は何を問う？ ～記号接地問題から「記号
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記号創発スタディノート#6 心は生成モデルで世界を予測する ～予測符号化・世界モデル・能動的推論
こんにちは、記号創発アウトリーチチームです。本連載「記号創発スタディノート」は、京都大学の谷口忠大（通称：たにちゅー）教授を中心に10年以上にわたり展開されてきた「記号創発システム論」について、その可能性と意義、中心的な手法、今後の展望についてコンパクトに解説するシリーズです。◆これまでの回：・第1回：なぜ、いま記号創発システム論なのか？ ～生成AI時代の「意味」の新学理へ・第2回：記号創発システム論は何を問う？ ～記号接地問題から「記
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記号創発スタディノート#5 記号創発を捉える数理モデル ～確率的生成モデルとは何か
こんにちは、記号創発アウトリーチチームです。本連載「記号創発スタディノート」は、京都大学の谷口忠大（通称：たにちゅー）教授を中心に10年以上にわたり展開されてきた「記号創発システム論」について、その可能性と意義、中心的な手法、今後の展望についてコンパクトに解説するシリーズです。◆これまでの回：・第1回：なぜ、いま記号創発システム論なのか？ ～生成AI時代の「意味」の新学理へ・第2回：記号創発システム論は何を問う？ ～記号接地問題から「記
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Featured labs
View all →Google DeepMind — Multi-Agent Research
PI: (Multiple PIs)
Multi-agent learning and emergent communication research at DeepMind, spanning cooperation, competition, language emergence, and societal-scale simulations of intelligent agents.
Theoretical Neurobiology Group (Friston Lab)
PI: Karl Friston
The Wellcome Trust Centre for Human Neuroimaging hosts the theoretical neurobiology group, which develops the free-energy principle and active inference as a unifying account of perception, action, and learning.
Human & Machine Learning Lab
PI: Brenden Lake
The lab develops computational models of how humans learn rich, structured concepts from limited experience, and how machines can do the same. Recent work has focused on systematic generalisation in neural networks.
Upcoming events
View all →Active Inference & Free Energy Principle Workshop
Jun 15, 2026 – Jun 17, 2026 · London, UK
Three-day workshop on the latest theoretical and applied developments in active inference and the free-energy principle. Mixed-format programme with invited talks, posters, and small-group tutorials.
CPC Reading Group — Summer Session
Jul 1, 2026 – Jul 29, 2026 · Online
A four-week online reading group covering recent CPC and active inference papers. Sessions alternate between English and Japanese facilitation; reading materials are bilingual where possible.
International Symposium on Symbol Emergence in Robotics 2026
Sep 12, 2026 – Sep 14, 2026 · Kyoto, Japan
Annual symposium on symbol emergence systems, covering theoretical and applied research in cognitive robotics. Tracks include MHNG, multimodal concept formation, embodied language acquisition, and multi-agent communication.
Recent on YouTube
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対談バトル！ アテンション・エコノミー時代の科学コミュニケーションとは？【丸山隆一 vs スズキ】
アテンション・エコノミー時代のいま、そして、これからの科学コミュニケーションはどうあるべきか、メタサイエンス ...
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対談バトル！ 著者襲来！ “予測誤差を食らう” ってなんなの？ 【行為する意識：吉田正俊 vs スズキ】
「予測誤差を食らう」とは何なのか、『行為する意識』の著者のひとりである吉田さんに直撃インタビューました！ 0:00 スタート ...
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対談バトル！ 哲学は現代科学と協働できるのか？【平井靖史 vs スズキ】
科学は現代科学と協働できるのか、進化生物学者が哲学者の平井さんに対談バトルを挑みました！ 【チャプター】 00:00 ...
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