How does this skill use Markov Blankets?

It uses Markov Blankets to define the boundary between an agent's internal model and the external world, determining whether to update beliefs (perceptual inference) or change the world (active inference).

Which programming languages are supported for implementation?

The skill provides ready-to-use implementation patterns and code snippets for Babashka (Clojure), Julia, and DuckDB SQL.

What is the connection to Paradigm's Multiverse Finance?

This skill implements Multiverse Finance logic to manage assets across parallel probability 'verses,' allowing for value extraction upon verse resolution and risk-free borrowing within specific outcomes.

Can this skill be used for network optimization?

Yes, it calculates spectral gaps and Ramanujan expander properties to bound the Price of Anarchy in network routing, influence propagation, and information flow.

What is World Extractable Value (WEV)?

WEV is a metric that quantifies the inefficiency in a system by measuring the gap between selfish equilibrium (Nash) and the socially optimal state, often expressed as PoA - 1.

World Extractable Value (WEV)

Name: World Extractable Value (WEV)
Author: plurigrid

byplurigrid

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数据科学与机器学习

Quantifies and extracts economic value from coordination inefficiencies and world transitions using Markov blanket arbitrage and Multiverse Finance.

关于

The World Extractable Value (WEV) skill is a specialized tool for Claude Code designed to analyze and exploit the gap between Nash equilibria and optimal system states. By integrating Tim Roughgarden’s Price of Anarchy with Karl Friston’s Free Energy Principle and Paradigm’s Multiverse Finance thesis, this skill enables developers to model parallel financial outcomes ('verses'), compute spectral gaps in networks, and implement active inference strategies. It is particularly useful for building decentralized coordination mechanisms, optimizing network routing, and managing risk in complex, multi-state financial environments through topological modeling.

主要功能

Maps coordination mechanisms like Correlated Equilibrium and Stackelberg games to WEV reduction
Provides standardized DuckDB schemas and Babashka/Julia snippets for WEV tracking
Integrates Paradigm’s Multiverse Finance for parallel universe asset management
Calculates Price of Anarchy (PoA) and spectral gaps for d-regular Ramanujan expanders
2 GitHub stars
Implements Markov Blanket logic to automate perceptual vs. active inference decisions

使用场景

Designing algorithmic game theory mechanisms that minimize coordination waste in DAOs
Modeling complex financial insurance and liquidity protocols using Multiverse Finance verses
Optimizing network topology for maximal information propagation and minimal surprise

关于

主要功能

Maps coordination mechanisms like Correlated Equilibrium and Stackelberg games to WEV reduction
Provides standardized DuckDB schemas and Babashka/Julia snippets for WEV tracking
Integrates Paradigm’s Multiverse Finance for parallel universe asset management
Calculates Price of Anarchy (PoA) and spectral gaps for d-regular Ramanujan expanders
2 GitHub stars
Implements Markov Blanket logic to automate perceptual vs. active inference decisions

使用场景

Designing algorithmic game theory mechanisms that minimize coordination waste in DAOs
Modeling complex financial insurance and liquidity protocols using Multiverse Finance verses
Optimizing network topology for maximal information propagation and minimal surprise