[[Bert Wang-Chak Chan]] is a Research Software Engineer at Google DeepMind (formerly Brain) with expertise in artificial life, complex systems, and evolutionary computation. His primary research interests lie in exploring the computational principles underlying self-organization, emergence, and open-ended evolution in artificial systems. He is particularly interested in utilizing [[continuous cellular automata]] (CAs) as a modeling framework for studying these phenomena.
Chan's notable contributions include:
2. **Introducing Lenia:** He developed Lenia, a family of continuous CAs that exhibit a remarkable capacity for generating life-like patterns and behaviors. Lenia has become a popular tool for studying artificial life and cellular automata dynamics.
4. **Open-Ended Evolution in Lenia:** He investigated the potential for open-ended evolution in Lenia, demonstrating the ability of Lenia systems to continuously adapt and diversify over time, leading to the emergence of novel and complex patterns.
6. **Exploring Morphogenesis and Autopoiesis:** He applied Lenia to model morphogenesis, the development of form and structure, and autopoiesis, the self-production of living systems, gaining insights into the underlying mechanisms of these processes.
Chan's work has been presented at numerous conferences and published in prestigious journals, including the Artificial Life Conference (ALIFE) and the Journal of Artificial Life (JAL). He has also received recognition for his contributions, including an Honorable Mention in the ALife Art Award and a Winner in the Genetic and Evolutionary Computation Conference (GECCO) Virtual Creatures Contest.
Chan's research holds promise for understanding the fundamental principles of self-organization, adaptation, and the emergence of complex systems. His work has implications for various fields, including artificial intelligence, robotics, and biology.
# References
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