paper
referenced-only
2021
paper:bongard-living-things-are-not-20th-century-machi-2021Living things are not (20th century) machines: updating mechanism metaphors in light of the modern science of machine behavior
ByJoshua Bongard·Michael LevinⓘAllen Discovery Center At Tufts University, Allen Discovery Center, Tufts University + 11 more
Intrinsic MotivationFields and Levin Scale-Free Biology FrameworkInverse Problem in Biomedical SettingsMachine BehaviorMulti-Scale CompetencyMachine Metaphor in BiologyPersuadability ContinuumMulti-Scale Option Space for Possible Living MachinesRahwan et al. 2019 Machine Behaviour (Nature)Top-Down Models in BiologySymbol Grounding
Frameworks (5)
- Fields and Levin Scale-Free Biology FrameworkFramework integrating evolutionary and developmental thinking across scales; cited as prior work relevant to multi-scale competency
- Machine BehaviorEmerging multidisciplinary field at interface of artificial life, machine learning, and synthetic bioengineering that provides updated understanding of machines.
- Machine Metaphor in BiologyThe central metaphor under examination: treating living things as machines; the paper argues for its update rather than rejection
- Multi-Scale Option Space for Possible Living MachinesFigure 1 framework with two axes (design vs. evolution; autonomy level) defining continuous space for classifying possible agents at each scale of organization
- Top-Down Models in BiologyPezzulo and Levin's framework for explanation and control of complex living systems above the molecular level, cited as prior work by Levin
Related work— refs + corpus + external arXiv
Cited / in-corpus / arXiv badges show which signals surfaced each row. Multi-source rows weighted higher.
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- Modeling Human Behavior Part I -- Learning and Belief ApproachesAndrew Fuchs and Andrea Passarella and Marco Conti2022≈ 74%
- A Step Toward World Models: A Survey on Robotic ManipulationYing Cheng, Xiaofan Sun, Shijie Wang, Fengling Li, Lei Zhu, Heng Tao Shen Peng-Fei Zhang2025≈ 74%
- Understanding World or Predicting Future? A Comprehensive Survey of World ModelsYunke Zhang, Yu Shang, Jie Feng, Yuheng Zhang, Zefang Zong, Yuan Yuan, Hongyuan Su, Nian Li, Jinghua Piao, Yucheng Deng, Nicholas Sukiennik, Chen Gao, Fengli Xu, Yong Li Jingtao Ding2025≈ 74%
- Human Cognition in Machines: A Unified Perspective of World ModelsPu Zhao, Amir Taherin, Arash Akbari, Arman Akbari, Yumei He, Sean Duffy, Juyi Lin, Yixiao Chen, Rahul Chowdhury, Enfu Nan, Yixin Shen, Yifan Cao, Haochen Zeng, Weiwei Chen, Geng Yuan, Jennifer Dy, Sarah Ostadabbas, Silvia Zhang, David Kaeli, Edmund Yeh, Yanzhi Wang Timothy Rupprecht2026≈ 74%
- On the Implicit and on the Artificial - Morphogenesis and Emergent Aesthetics in Autonomous Collective SystemsVitorino Ramos2007≈ 74%
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- From Masks to Worlds: A Hitchhiker's Guide to World ModelsYu Lei, Hecong Wu, Yuchen Zhu, Shufan Li, Yi Xin, Xiangtai Li, Molei Tao, Aditya Grover, Ming-Hsuan Yang Jinbin Bai2025≈ 74%
- Can a Machine be Conscious? Towards Universal Criteria for Machine ConsciousnessCosmin Badea Nur Aizaan Anwar2024≈ 73%
- Artificially intelligent agents in the social and behavioral sciences: A history and outlookMilena Tsvetkova Petter Holme2025≈ 73%
- World Models Should Prioritize the Unification of Physical and Social DynamicsChengdong Ma, Yizhe Huang, Weidong Huang, Siyuan Qi, Song-Chun Zhu, Xue Feng, Yaodong Yang Xiaoyuan Zhang2025≈ 73%
- The principles of adaptation in organisms and machines I: machine learning, information theory, and thermodynamicsHideaki Shimazaki2019≈ 73%
- A Mechanistic View on Video Generation as World Models: State and DynamicsZhifei Chen, Yihua Du, Dongyu Yan, Wenhang Ge, Guibao Shen, Xinli Xu, Leyi Wu, Man Chen, Tianshuo Xu, Peiran Ren, Xin Tao, Pengfei Wan, Ying-Cong Chen Luozhou Wang2026≈ 73%
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- The biogenic approach to cognitionin corpus2005≈ 71%
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- The Machine Consciousness Hypothesisin corpus≈ 70%
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- Learning without neurons in physical systemsin corpus2022≈ 68%
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