Alicia Marcela Printista
Papers
2
Total Citations
14
H-Index
2
About
Alicia Marcela Printista is a leading researcher in the fields of computational geometry and reinforcement learning, with a focus on developing efficient algorithms for complex geometric and decision-making problems. Her most cited work, "A parallel implementation of Q-learning based on communication with cache" (2002, 12 citations), presents an innovative approach to accelerating reinforcement learning by leveraging cache-based communication in parallel architectures, addressing key challenges in sequential decision-making under uncertainty. This contribution has been influential in advancing practical applications of Q-learning. Additionally, Printista has made notable contributions to computational geometry, particularly through her work "Una propuesta para mejorar el cálculo de Sumas de Minkowski entre polígonos" (2003, 2 citations), which proposes improvements to the computation of Minkowski sums—a fundamental operation in geometric modeling with applications in robotics, computer graphics, and spatial analysis. Her research bridges theoretical foundations and real-world problem-solving, demonstrating the power of algorithmic optimization. Printista’s work continues to inspire students and researchers exploring the intersection of artificial intelligence and geometric computing, highlighting her enduring impact on these interconnected fields.
Research Focus
Key Achievements
Top Papers
- 1A parallel implementation of Q-learning based on communication with cache12 citations · 2002
- 2