Dynamical Perception-Action Loop Formation with Developmental Embodiment for Hierarchical Active Inference
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There is no standardized way of defining environments for Active Inference agents.
“In general, we observe that there is no standardized way of defining environments for Active Inference agents.”
From Reactive Environments for Active Inference Agents with RxEnvironments.jl (2025) · cites this paper as [5]
Cites
The free-energy principle: a unified brain theory?
Friston, K. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2787 · Cited by 8,120 · see citing works
Active inference: a process theory
Friston, K., FitzGerald, T., Rigoli, F., Schwartenbeck, P., & Pezzulo, G. (2017) · Neural Computation · doi:10.1162/neco_a_00912 · Cited by 1,156 · see citing works
Computational psychiatry: the brain as a phantastic organ
Friston, K. J., Stephan, K. E., Montague, R., & Dolan, R. J. (2014) · The Lancet Psychiatry · doi:10.1016/s2215-0366(14)70275-5 · Cited by 531 · see citing works
The Markov blankets of life: autonomy, active inference and the free energy principle
Kirchhoff, M., Parr, T., Palacios, E., Friston, K., & Kiverstein, J. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2017.0792 · Cited by 463 · see citing works
Deeply Felt Affect: The Emergence of Valence in Deep Active Inference
Hesp, C., Smith, R., Parr, T., Allen, M., Friston, K. J., & Ramstead, M. J. D. (2021) · Neural Computation · doi:10.1162/neco_a_01341 · Cited by 246 · see citing works
Active inference on discrete state-spaces: A synthesis
Da Costa, L., Parr, T., Sajid, N., Veselic, S., Neacsu, V., & Friston, K. (2020) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2020.102447 · Cited by 226 · see citing works
Ueltzhöffer, K. (2018) · Biological Cybernetics · doi:10.1007/s00422-018-0785-7 · Cited by 98 · see citing works
Active Inference and Behavior Trees for Reactive Action Planning and Execution in Robotics
Pezzato, C., Corbato, C. H., Bonhof, S., & Wisse, M. (2023) · IEEE Transactions on Robotics · doi:10.1109/tro.2022.3226144 · Cited by 44 · see citing works
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Reactive Environments for Active Inference Agents with RxEnvironments.jl
Nuijten, W. W. L., & de Vries, B. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-77138-5_10
“While some implementations use Gymnasium [24,17,20], others use specialized toolboxes for implementing Active Inference agents for their environment simulation [5,10].”
- Authors
- Esaki, K., Matsumura, T., Minusa, S., Shao, Y., Yoshimura, C., & Mizuno, H.
- Affiliations
- Hitachi (Japan) (JP)
- Corresponding author
- Esaki, Kanako
- Venue
- Communications in Computer and Information Science
- Publisher
- Springer Nature Switzerland
- Published
- 2023-11-16
- Pages
- 14-28
- ISSN
- 1865-0929 (ISSN-L)
- 1865-0937
- OpenAlex
- W4388693555
- Cited by
- 4
- References
- 8
- Citations by year
- 2026: 1 · 2024: 3
- FWCI
- 2.06
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- Communications in computer and information science (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Embodied and Extended Cognition
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Keywords
- perception-action loop, embodied cognition, robotic arm control, joint selection, autonomous systems
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