Carlos F. de Brito
Papers
2
Total Citations
12
H-Index
2
About
Carlos F. de Brito is a researcher at the intersection of artificial life, evolutionary robotics, and virtual character animation. His work challenges conventional approaches to generating autonomous behavior by drawing inspiration from embodied and enactive AI—the idea that natural, lifelike behavior emerges not from pre-programmed scripts, but from the dynamic coupling between an agent’s internal mechanisms and its environment. In his most cited work, "Evolving Plastic Neuromodulated Networks for Behavior Emergence of Autonomous Virtual Characters" (2013, 7 citations), de Brito pioneered the use of neuromodulated neural networks—plastic systems that can adapt their own connection weights—to evolve virtual characters capable of exhibiting spontaneous, context-sensitive behaviors. A follow-up paper, "Emergence of Autonomous Behaviors of Virtual Characters through Simulated Reproduction" (2013, 5 citations), further demonstrated how simulated evolution and reproduction can yield agents whose actions arise from internal dynamics rather than external control. Though his citation counts are modest, de Brito’s contributions are conceptually significant: he provides a principled, bio-inspired framework for creating truly autonomous virtual beings, offering a compelling alternative to scripted animation and reinforcement learning. His work is essential reading for researchers in evolutionary robotics, artificial life, and character animation seeking to understand how minimal, embodied mechanisms can generate rich, emergent behavior.
Research Focus
Key Achievements
Top Papers
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