What types of Cellular Automata (CA) does this skill support?

It supports a wide spectrum of CA, ranging from classic Wolfram rules to continuous Lenia, Neural Cellular Automata (NCA), and mass-conserving Flow-Lenia.

Does it provide mathematical formulations for evolutionary biology?

Absolutely. It includes equations for fitness-proportionate selection, replicator dynamics, Wright-Fisher drift, and mutation-selection balance.

Can I use this for multi-agent social simulations?

Yes, it includes frameworks for agent-based models like Sugarscape and DeepMind's Concordia for creating LLM-driven generative agent societies.

Does this skill include information on GPU-accelerated ALife?

Yes, it provides resources and implementation patterns for CUDA-based particle engines like ALIEN and JAX-accelerated libraries like Leniax and CAX.

ALife Simulation & Modeling

Name: ALife Simulation & Modeling
Author: plurigrid

byplurigrid

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数据科学与机器学习

Provides comprehensive resources, mathematical models, and implementation patterns for simulating artificial life, evolutionary dynamics, and emergent systems.

关于

This skill transforms Claude into an expert in Artificial Life (ALife), integrating state-of-the-art research from the ALIFE2025 proceedings with foundational concepts from classic texts like Axelrod's 'Evolution of Cooperation' and Epstein-Axtell's 'Sugarscape.' It provides users with the mathematical frameworks and code snippets for replicator dynamics, cellular automata (Lenia, NCA), agent-based modeling (ABM), and swarm intelligence. Whether you are building CUDA-powered particle engines, exploring mass-conserving flow-lenia, or designing LLM-driven generative agent societies using DeepMind's Concordia, this skill offers the theoretical depth and implementation patterns required for advanced complex systems research.

主要功能

Integrate chemical computing patterns such as the Belousov-Zhabotinsky (BZ) oscillator.
2 GitHub stars
Model evolutionary game theory using Axelrod’s TIT-FOR-TAT and replicator dynamics.
Apply swarm intelligence and Boid rules for emergent behavior and collective motion.
Design agent-based models (ABMs) for social simulation, trade, and resource distribution.
Implement diverse cellular automata including Lenia, Neural CA, and mass-conserving Flow-Lenia.

使用场景

Developing self-organizing patterns and biological simulations using continuous cellular automata.
Simulating social and economic emergence through generative agent-based models and Sugarscape patterns.
Researching open-ended evolution and fitness landscapes for artificial organisms and malware evolution.

关于

主要功能

Integrate chemical computing patterns such as the Belousov-Zhabotinsky (BZ) oscillator.
2 GitHub stars
Model evolutionary game theory using Axelrod’s TIT-FOR-TAT and replicator dynamics.
Apply swarm intelligence and Boid rules for emergent behavior and collective motion.
Design agent-based models (ABMs) for social simulation, trade, and resource distribution.
Implement diverse cellular automata including Lenia, Neural CA, and mass-conserving Flow-Lenia.

使用场景

Developing self-organizing patterns and biological simulations using continuous cellular automata.
Simulating social and economic emergence through generative agent-based models and Sugarscape patterns.
Researching open-ended evolution and fitness landscapes for artificial organisms and malware evolution.