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Found 7 papers, 4 papers with code
Discovering Sensorimotor Agency in Cellular Automata using Diversity Search
The research field of Artificial Life studies how life-like phenomena such as autopoiesis, agency, or self-regulation can self-organize in computer simulations.
Meta-Diversity Search in Complex Systems, A Recipe for Artificial Open-Endedness ?
Holmes incrementally learns a hierarchy of modular representations to characterize divergent sources of diversity and uses a goal-based intrinsically-motivated exploration as the diversity search strategy.
SBMLtoODEjax: Efficient Simulation and Optimization of Biological Network Models in JAX
Advances in bioengineering and biomedicine demand a deep understanding of the dynamic behavior of biological systems, ranging from protein pathways to complex cellular processes.
Flow-Lenia: Towards open-ended evolution in cellular automata through mass conservation and parameter localization
Finally, we show that Flow Lenia enables the integration of the parameters of the CA update rules within the CA dynamics, making them dynamic and localized, allowing for multi-species simulations, with locally coherent update rules that define properties of the emerging creatures, and that can be mixed with neighbouring rules.
Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic Systems
Self-organization of complex morphological patterns from local interactions is a fascinating phenomenon in many natural and artificial systems.
Progressive growing of self-organized hierarchical representations for exploration
A central challenge is how to learn incrementally representations in order to progressively build a map of the discovered structures and re-use it to further explore.
Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems
Using a continuous GOL as a testbed, we show that recent intrinsically-motivated machine learning algorithms (POP-IMGEPs), initially developed for learning of inverse models in robotics, can be transposed and used in this novel application area.
