Papers
5
Total Citations
203
H-Index
5
About
David Luviano-Cruz is a leading researcher at the intersection of swarm intelligence, multi-agent systems, and decision-making. His work is defined by pioneering the use of evolutionary algorithms and reinforcement learning to solve complex coordination problems. His landmark review, "PSO, a Swarm Intelligence-Based Evolutionary Algorithm as a Decision-Making Strategy," has garnered 82 citations, establishing a foundational framework for applying metaheuristics to organizational data analysis. Dr. Luviano-Cruz has made significant contributions to autonomous navigation, developing novel path-planning algorithms for multi-agent systems in unknown environments. His 2016 paper on neural kernel smoothing and reinforcement learning (70 citations) and his subsequent work on continuous-time fuzzy reinforcement learning (30 citations) have been instrumental in enabling cooperative mobile robots to learn adaptive behaviors without pre-programmed rules. More recently, his 2025 analysis on bridging remote operations with augmented reality (8 citations) signals a forward-looking focus on human-machine interaction in hazardous environments. With a career spanning foundational theory to cutting-edge applications, Dr. Luviano-Cruz’s research continues to shape how intelligent systems collaborate and make decisions in dynamic, real-world settings.
Research Focus
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