2 repositorios
Simulations used to study irreversibility, entropy growth, and system complexity.
Distinct from Complexity Scaling: None of the candidates cover entropy growth and irreversibility simulations; they focus on polygon modeling or algorithmic complexity.
Explore 2 awesome GitHub repositories matching scientific & mathematical computing · Complexity Dynamics Simulations. Refine with filters or upvote what's useful.
Mesa is a Python framework for agent-based modeling and complex systems simulation. It provides a toolkit for creating simulations where autonomous agents interact within a shared environment to observe emergent global behaviors. The project includes a browser-based interface for real-time visualization of simulation states and agent interactions. It also functions as a data analysis library for recording and processing metrics from model runs to quantify system behavior. The framework supports multiple environmental topologies, including grid-based spatial mapping and network-graph topologi
Models individual agent rules to observe the development of global patterns and emergent behaviors over time.
This project is a collection of deep learning research implementations and a reproduction kit designed to translate theoretical AI papers into working code. It provides a library of neural network architectures and reference implementations for reproducing seminal research concepts through interactive notebooks. The repository distinguishes itself through the implementation of AI theory and scaling laws, covering complexity dynamics, information theory, and the simulation of universal AI agents. It also includes a benchmarking suite for synthetic reasoning, allowing for the evaluation of mode
Simulates cellular automata and entropy growth to analyze irreversibility and complexity dynamics.