paper
referenced-only
2020
paper:e-reconciling-emergences-an-information-th-2020Reconciling emergences: An information-theoretic approach to identify causal emergence in multivariate data
ByF. E. Rosas·P. A. M. Mediano·H. J. Jensen·A. K. Seth·A. B. Barrett·R. L. Carhart-Harris+1 more
Related work— refs + corpus + external arXiv
Cited / in-corpus / arXiv badges show which signals surfaced each row. Multi-source rows weighted higher.
- ≈ 77%
- Emergence and Causality in Complex Systems: A Survey on Causal Emergence and Related Quantitative Studiesin corpus2023≈ 76%
- ≈ 73%
- Choosing with unknown causal information: Action-outcome probabilities for decision making can be grounded in causal modelsDavid Danks, Hugo J. Escalante Balderas, L. Enrique Sucar Mauricio Gonzalez Soto2026≈ 73%
- Causal Structure Learning: a Bayesian approach based on random graphsIvan R. Feliciano-Avelino, L. Enrique Sucar, Hugo J. Escalante Balderas Mauricio Gonzalez-Soto2026≈ 72%
- Emergence of Theory of Mind Collaboration in Multiagent SystemsZipeng Fu, Linqi Zhou, Kexin Yang, Song-Chun Zhu Luyao Yuan2021≈ 72%
- ≈ 72%
- Causal Bayesian Optimization via Exogenous Distribution LearningZihao Wang, Yuzhou Chen, Xiaoning Qian Shaogang Ren2026≈ 72%
- Causal Emergence of Consciousness through Learned Multiscale Neural Dynamics in MiceYingqi Rong, Kaiwei Liu, Mingzhe Yang, Jiang Zhang, Jing He Zhipeng Wang2025≈ 72%
- A macro agent and its actionsFrancesco Massari, Maggie Beheler-Amass and Giulio Tononi Larissa Albantakis2020≈ 72%
- ≈ 72%
- Local Causal Discovery with Linear non-Gaussian Cyclic ModelsIgnavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang Haoyue Dai2024≈ 71%
- Causal Foundations of Collective AgencySebastian Weichwald, Lewis Hammond Frederik Hytting J{\o}rgensen2026≈ 71%
- ≈ 71%
- Two Ways of Understanding Social Dynamics: Analyzing the Predictability of Emergence of Objects in Reddit r/place Dependent on Locality in Space and TimeJavier Fernandez, Olaf Witkowski Alyssa M Adams2022≈ 71%
- The Birth of Knowledge: Emergent Features across Time, Space, and Scale in Large Language ModelsMicah Adler, Nir Shavit Shashata Sawmya2025≈ 71%
- Attributing Emergence in Million-Agent SystemsJilin Mei, Qian Chen, Qihan Ren, Linfeng Zhang, Quanshi Zhang, Jing Shao, Xia Hu, Dongrui Liu Ling Tang2026≈ 71%
- ≈ 69%
- Design for an Individual: Connectionist Approaches to the Evolutionary Transitions in Individualityin corpus2022≈ 68%
- Information, Processes and Gamesin corpus≈ 68%
- ≈ 67%
- ≈ 67%
- Collective intelligence: A unifying concept for integrating biology across scales and substratesin corpus2024≈ 66%
- ≈ 66%
- ≈ 66%
- ≈ 66%
- Active Inference, Curiosity and Insightin corpus2017≈ 66%
- Cognitive glues are shared models of relative scarcities: the economics of collective intelligencein corpus2026≈ 66%
- ≈ 65%
- ≈ 65%
Similar preprints — Semantic Scholar
Cited by (1)
- The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents
Causal emergence in the latent-space representations of reinforcement learning agents is consistently predictive of final reward and aligns dynamically with reward improvement across training — a find