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.
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
Sophisticated Learning Implementations: MATLAB and Python code for the "Sophisticated Learning" algorithm from Hodson et al.'s research on model-based planning.
Archive of active inference agents based on reactive message passing.
Design of an acrobot stabilization controller using active inference.
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.
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