NashCalc: Building the Desmos of Game Theory
NashCalc lays the groundwork for a Desmos-style learning environment for game theory, turning abstract payoff matrices and computational solvers into an interactive visual experience. For students early in their learning journey, many existing tools require writing code or interpreting results with little visual explanation; NashCalc is designed to lower that barrier. Powered by Gambit and Nashpy, the current prototype supports two-player N × N normal-form games.
Financial Network Viz
This visualization uses Python's NetworkX and Matplotlib with the Bellman-Ford algorithm to identify negative cycles in directed graphs of currency pairs, revealing potential arbitrage opportunities within and across exchanges.
