Ricky Yudianto

Institut Sains dan Teknologi Terpadu Surabaya

Papers

Total Citations

H-Index

About

Ricky Yudianto is a researcher in artificial intelligence and game theory, with a focus on developing intelligent agents for strategic gameplay. His most cited work, "Evolutionary Neural Network for Othello Game" (2012), explores the integration of evolutionary algorithms with neural networks to create adaptive AI capable of competing against human players. This research addresses fundamental challenges in AI, including modeling human decision-making processes and translating cognitive strategies into computational systems. While his citation count—4 for this paper—reflects a niche but dedicated audience, Yudianto’s contributions lie in bridging evolutionary computation and game-based AI, offering insights into how machines can learn and optimize strategies through iterative adaptation. His work is particularly relevant for students and researchers interested in neuroevolution, game AI, and the intersection of biological inspiration and artificial intelligence. Yudianto’s research underscores the enduring value of classic games like Othello as testbeds for developing and evaluating intelligent systems, making his findings a stepping stone for further exploration in adaptive AI and human-machine interaction.