Towards information based spatiotemporal patterns as a foundation for agent representation in dynamical systems
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Abstract (arXiv)
We present some arguments why existing methods for representing agents fall short in applications crucial to artificial life. Using a thought experiment involving a fictitious dynamical systems model of the biosphere we argue that the metabolism, motility, and the concept of counterfactual variation should be compatible with any agent representation in dynamical systems. We then propose an information-theoretic notion of integrated spatiotemporal patterns which we believe can serve as the basic building block of an agent definition. We argue that these patterns are capable of solving the problems mentioned before. We also test this in some preliminary experiments.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 May 2016.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 0; 2024: 1.
5 papers.
- 2024Discovering Sensorimotor Agency in Cellular Automata using Diversity Searchcited by 9
- 2022Interpreting systems as solving POMDPs: a step towards a formal understanding of agencycited by 7
- 2021Interpreting Dynamical Systems as Bayesian Reasonerscited by 5
- 2021Embodiment and Computational Creativitycited by 3
- 2022Hybrid Life: Integrating Biological, Artificial, and Cognitive Systemscited by 3
- 2024Discovering Sensorimotor Agency in Cellular Automata using Diversity Search14 Feb 2024
- 2022Hybrid Life: Integrating Biological, Artificial, and Cognitive Systems1 Dec 2022
- 2022Interpreting systems as solving POMDPs: a step towards a formal understanding of agency4 Sep 2022
- 2021Interpreting Dynamical Systems as Bayesian Reasoners27 Dec 2021
- 2021Embodiment and Computational Creativity2 Jul 2021