AI, Game Theory, and Algorithms
I am a programmer passionate about problem-solving and algorithm development. My AI research spans computer vision and reinforcement learning, with a strong interest in multi-agent systems, RL applications in robotics and games, and algorithm optimization.
Some Of My Latest Work
AI Market Entry Strategy
We apply reinforcement learning (RL) to market entry and exit strategies, demonstrating that RL agents outperform rule-based approaches in maximizing capital. Our findings highlight RL's potential to uncover novel insights in microeconomic strategy.
AI Codenames
We use AI bots, vector embeddings, and cosine distance to demonstrate AI's effectiveness in the board game Codenames. A Spymaster leverages learned embeddings to generate clues, guiding both human and bot players in identifying their team's spies.
Unsupervised Polish Handwriting Recognition
We leverage an HWR model as a generator in a GAN network to predict Polish text from segmented image snippets. With no labels for these image snippets, we hope to show that the generator learns to model the distribution of real Polish text downloaded from the internet, enabling robust handwriting recognition without labeled training data.