At Minoan Lab, we delve into the intricate world of Game Theory, Optimization, and Theoretical Computer Science, exploring the mathematical and computational foundations that drive decision-making in complex systems. Our research bridges the timeless elegance of theory with the ever-growing demands of modern machine learning and artificial intelligence, uncovering the principles that govern strategic interactions in multi-agent environments.

One of the cornerstones of our approach is dynamical systems, whose interplay with theoretical computer science and machine learning unveils deep insights into equilibrium computation, learning in games, and robustness in optimization. By studying how systems evolve over time—whether in competitive markets, distributed algorithms, or intelligent agents adapting to uncertainty—we aim to illuminate the underlying structure of decision-making and intelligence.

In an era where AI and automation shape the world around us, understanding the mathematical fabric of decision processes is more crucial than ever. Proofs are not just formalities; they are the guiding light that separates intuition from truth, ensuring that our models are principled, reliable, and interpretable. The beauty of theoretical research lies in its ability to provide fundamental guarantees—statements that hold regardless of empirical trends, architectures, or fleeting heuristics.

Exploring this domain is not just an academic pursuit; it is an intellectual adventure into the heart of reasoning and computation. Whether in designing fair and efficient algorithms, understanding the dynamics of strategic interactions, or optimizing systems with provable guarantees, our lab thrives on uncovering truths that stand the test of time.