The field of dynamical systems and network analysis is witnessing a significant shift towards the study of complex behaviors and emergent properties in various systems. Researchers are increasingly focusing on the impact of update modes and synchronism on the dynamics of cellular automata and Boolean networks. The development of new classification frameworks and analysis methods is enabling a deeper understanding of the intricate relationships between system components and their collective behavior. Notably, the use of curiosity-driven AI scientists and continuous Petri nets is providing new insights into the self-organization of complex systems and the refinement of biological networks. Some noteworthy papers in this area include:

• Impact of (a)Synchronism on ECA: Towards a New Classification, which presents a novel classification of elementary cellular automata based on their dynamics under different update schemes.
• Continuous Petri Nets Faithfully Fluidify Most Permissive Boolean Networks, which establishes a formal link between Most Permissive Boolean networks and their continuous dynamical refinements.