An algorithm to calculate all pure strategy Nash equilibria in multi-objective games with quasiconvex utility functions
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Updated
May 24, 2022 - Python
An algorithm to calculate all pure strategy Nash equilibria in multi-objective games with quasiconvex utility functions
Algorithms for computing or learning equilibria in multi-objective games
An AI that plays Tic-Tac-Toe using the Minimax algorithm, ensuring it always wins or draws. Demonstrates optimal decision-making and game logic implementation.
Correlated Equilibrium and Mixed Nash Equilibrium with python
This project earned me 2nd place in the IEEE Event at APOGEE 2024, the technical fest of BITS Pilani. The competition revolved around Strategy Comparison Games, incorporating a unique twist: a dynamic payoff matrix with added noise in communication.
Repo associated with the paper: Algorithmic Collusion And The Minimum Price Markov Game
Work-throughs of qiskit/pyquil quantum computing tutorials & exercises
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