How does it relate to standard Reinforcement Learning (RL)?

It maps RL concepts like PPO losses and entropy bonuses to Active Inference concepts like Variational Free Energy (VFE) and mean field updates, showing the mathematical convergence of both fields.

What is the difference between PAD and EFE in this skill?

Perception/Action Divergence (PAD) utilizes an entropy regularizer—meaning it focuses on uncertainty awareness—whereas Expected Free Energy (EFE) includes mutual information for exploration.

What is the core benefit of this skill for robotics?

It provides a principled theoretical framework for robot control by treating locomotion as a process of minimizing surprise about future sensory observations through predictive distribution modeling.

Can it be used for Sim2Real applications?

Yes, it specifically integrates with the MuJoCo Playground and K-Scale’s stack to handle the transition from simulated inference to real-world motor execution.

Which frameworks are primarily supported?

The skill focuses on JAX-based implementations (MJX), MuJoCo physics, and the K-Scale Labs software ecosystem including ksim and kinfer.

Active Inference Robotics

Name: Active Inference Robotics
Author: plurigrid

byplurigrid

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데이터 과학 및 ML

Synthesizes Patrick Kenny's discrete active inference framework with K-Scale's JAX/MuJoCo stack for predictive robot control.

This skill bridges theoretical active inference with practical robotics by integrating Patrick Kenny's discrete framework with the K-Scale JAX/MuJoCo ecosystem. It allows Claude to assist in developing locomotion policies that treat action as a process of minimizing surprise about future sensations. By mapping complex concepts like Mean Field Approximation and Variational Free Energy to standard Reinforcement Learning implementations like PPO and state estimation, this skill provides a principled approach to Sim2Real transfer and hierarchical robot control architectures.

주요 기능

01Provides domain-specific guidance for the K-Scale (ksim, kos, kinfer) ecosystem.

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03Maps Active Inference concepts (VFE, EFE) to standard RL training loops and PPO updates.

04Facilitates Sim2Real workflows using the MuJoCo Playground framework.

05Implements hierarchical patterns for reflexive control and deliberative planning.

06Synthesizes Patrick Kenny's PAD (Perception/Action Divergence) criterion with JAX-based robotics.

사용 사례

01Developing predictive coding policies for humanoid robot locomotion.

02Building hierarchical state estimation models for complex robotic environments.

03Bridging KL divergence minimization theories with JAX-based RL training.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi active-inference-robotics

For use in Claude.ai and ChatGPT

Download Skill