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Titlebook: Cellular Automata; 15th International C Bastien Chopard,Stefania Bandini,Mira Arabi Haddad Conference proceedings 2022 The Editor(s) (if ap

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21#
發(fā)表于 2025-3-25 05:18:10 | 只看該作者
Algebras of Undirected Wiring Diagramsence by using local mappings to obtain millions of 5-state solution, one of them using 58 transitions. It is based on the solution of Kamikawa and Umeo that uses 6 states and 74 transitions. Then, we explain in which sense even bigger classes of problems can be considered.
22#
發(fā)表于 2025-3-25 08:50:30 | 只看該作者
23#
發(fā)表于 2025-3-25 11:58:41 | 只看該作者
Airway Management in Trauma Patientsoutput of the quantum circuit and the CA rule. We also inspect the differences observed when changing the number of gates and the mutation rate. We benchmark our methods with stochastic as well as deterministic CA rules, and briefly discuss the possible extensions their quantum “cousins” may enable.
24#
發(fā)表于 2025-3-25 17:59:24 | 只看該作者
25#
發(fā)表于 2025-3-25 23:08:49 | 只看該作者
Millions of?5-State ,-Real Time Sequence Generators via?Local Simulationsence by using local mappings to obtain millions of 5-state solution, one of them using 58 transitions. It is based on the solution of Kamikawa and Umeo that uses 6 states and 74 transitions. Then, we explain in which sense even bigger classes of problems can be considered.
26#
發(fā)表于 2025-3-26 04:02:51 | 只看該作者
27#
發(fā)表于 2025-3-26 04:42:51 | 只看該作者
Evolving Quantum Circuits to Implement Stochastic and Deterministic Cellular Automata Rulesoutput of the quantum circuit and the CA rule. We also inspect the differences observed when changing the number of gates and the mutation rate. We benchmark our methods with stochastic as well as deterministic CA rules, and briefly discuss the possible extensions their quantum “cousins” may enable.
28#
發(fā)表于 2025-3-26 12:18:39 | 只看該作者
29#
發(fā)表于 2025-3-26 16:23:35 | 只看該作者
https://doi.org/10.1007/978-3-319-94929-1ithms have been used extensively to generate CA based S-boxes. Here we explore the use of Reinforcement Learning algorithms that uses relatively well understood and mathematically grounded framework of Markov Decision Processes as an alternative to genetic programming.
30#
發(fā)表于 2025-3-26 18:16:58 | 只看該作者
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