Game Theory Cheat Sheet
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Updated
May 4, 2023
Game Theory Cheat Sheet
PyDiffGame is a Python implementation of a Nash Equilibrium solution to Differential Games, based on a reduction of Game Hamilton-Bellman-Jacobi (GHJB) equations to Game Algebraic and Differential Riccati equations, associated with Multi-Objective Dynamical Control Systems
Computing mixed-strategy Nash Equilibria for games involving multiple players
Implementing different learning algorithms and analyzing their performance in a Markov game model called the Soccer Game
Game Theoretic Representation of Economic Experiments
MasterAI decisively defeated 14 top human Texas hold'em poker professsionals in September 2020.
Implementation of the Nash Q-Learning algorithm to solve simple MARL problems with two agents.
This repository analyses Strategic form games for N-player calculating various Equilibrium's, Calculate MSNE for 2-Player strategic form and zero sum game, Also contains algorithm for N-player finite Mechanism design to check if social choice function is SDSE, Ex-Post-efficient and Non-dictatorial.
Finds nash equilibria in strategic games by solving linear complementarity problems (LCP).
Equilibrium Verification Environment (EVE) is a formal verification tool for the automated analysis of temporal equilibrium properties of concurrent and multi-agent systems.
My thesis code for the Computer Engineering Master in NTUA
PSO for Nash Equilibrium. This is the code for my undergraduate thesis.粒子群算法求解纳什均衡
Simulation of agents competing for resources with different strategies
A Python implementation of game theory algorithms.
Bachelor Thesis on "Evaluating regrets while joining a community - A Novel Community Detection in Large Networks using Game Theory."
A GUI-tool for computing Nash flows over time with or without spillback as well as (spillback) thin flows.
This 'Generative Adversarial Network' project was implemented in grad course CSE-676 : Deep Learning [Fall 2019 @UB_SUNY] Course Instructor : Sargur N. Srihari(https://cedar.buffalo.edu/~srihari/)
Implementation of Deep Convolutional Generative Adversarial Networks in Pytorch and Tensorflow
A deep neural network to find Nash equilibria of normal-form stage games
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