Deep active inference agents using Monte-Carlo methods
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Updated
Oct 19, 2021 - Python
Deep active inference agents using Monte-Carlo methods
PyHGF: A neural network library for predictive coding
Active inference agent and corresponding environment in Unity used in the study "A deep active inference model of the rubber-hand illusion"
PID-like control implemented as active inference with linear generative models
Minimal model of tool discovery and tool innovation using active inference
[NeurIPS 2021] Contrastive learning formulation of the active inference framework, for matching visual goal states.
Implementation/simulation of active neural generative coding (ANGC) for training neurobiologically-plausible active inference agent models.
DIE — is an Artificial Life project aimed at reproducing emergence of distributed intelligence under environmental pressures using learning cellular automata models.
A Bayesian cruise controller. A minimal model of velocity regulation for a block on a frictionless surface.
Sophisticated Learning Implementations: MATLAB and Python code for the "Sophisticated Learning" algorithm from Hodson et al.'s research on model-based planning.
This repository focused on enhancing the Active Inference Controller (AIC) for robotic manipulation tasks on an Interbotix PincherX 150 5-DOF Robot. A modified control framework called the Reactive Active Inference Controller (ReAIC) outperfors the AIC in adaptation experiments.
Deep Active Inference of Mountain Car Problem
Archive of active inference agents based on reactive message passing.
Code, figures, animations for a NARX-EFE based agent.
Homing Piegon is an inference framework implementing Variational Message Passing. It can be used to implement an Active Inference agent that performs planning using a Tree Search algorithm that can been seen as a form of Bayesian Model Expansion.
Application of active inference to reinforcement learning.
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