pengoovvoo's starred repositories
Stackelberg-Game-Theory-Based-Optimization-Model-
This is the code provided to support the paper of "Stackelberg Game Theory Based Optimization Model for the Design of Payment Mechanism in Performance-Based PPPs"
Supports_for_AEPS
电力系统自动化《考虑电动汽车可调度潜力的充电站两阶段市场投标策略》源代码
stackelberg_Game
主从博弈 下层KKT条件 强对偶处理双线性
PyDiffGame
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
Game-Theory-Complex-Network
This project aims to explore the behavior of four evolutionary games, namely weak prisoner’s dilemma, stag hunt, snowdrift, and hawk dove, on different network topologies using various update rules. The analysis focuses on understanding how network structure and update rules influence the evolution of cooperation in complex systems.
Bayesian-Stackelberg-Games
The three algorithms used to solve Bayesian Stackelberg Games have been implemented here.
game_theory
Implementing Algorithms for Computing Stackelberg Equilibria in Security Games
stationary
:repeat: Stationary distributions for arbitrary finite state Markov processes, including specializations for the Moran, Wright-Fisher, and other processes, exact (when possible) and approximate computations
EpidemicModeling
Epidemic modeling combining a SIS (Susceptible-Infected-Susceptible) model over a Barabàsi-Albert complex network with a game-theory based vaccination strategy for each node.
Game-theoretic-network-simulator
GTNS is a discrete-event network simulator targeted primarily for research and educational use. GTNS is written in Visual C++ programming language and supports different network topologies. This simulator was first produced to implement locally multipath adaptive routing (LMAR) protocol, classified as a new reactive distance vector routing protocol for MANETs. LMAR can find an ad-hoc path without selfish nodes and wormholes using an exhaustive search algorithm in polynomial time. Also when the primary path fails, it discovers an alternative safe path if network graph remains connected after eliminating selfish/malicious nodes. The key feature of LMAR to seek safe route free of selfish and malicious nodes in polynomial time is its searching algorithm and flooding stage that its generated traffic is equi-loaded compared to single-path routing protocols but its security efficiency to bypass the attacks is much better than the other multi-path routing protocols. LMAR concept is introduced to provide the security feature known as availability and a simulator has been developed to analyze its behavior in complex network environments [1]. Then we have added detection mechanism to the simulator, which can detect selfish nodes in network. The proposed algorithm is resilient against collision and can be used in networks which wireless nodes use directional antennas and it also defend against an attack that malicious nodes try to break communications by relaying the packets in a specific direction. Some game theoretic strategies to enforce cooperation in network have been implemented in GTNS, for example Forwarding-Ratio Strategy, TFT-Strategy and ERTFT. This tutorial helps new users to get familiar with GTNS and run different network scenarios.
networkx-guide
We here are very big fans of NetworkX as a graph library and its comprehensive set of graph algorithms. For many though, working with NetworkX involves a steep learning curve. This guide is designed as an aid for beginners and experienced users to find specific tips and explore the world of complex networks.
Modeling_complex_networks
Modeling complex networks: An implementation based on Python+NetworkX
Complex_Networks
Simulate complex networks with different models(small world, scale-free, random), and compare the robustness (under random failures) of them.
Complex-Network
复杂网络研究资源整理和基础知识学习