Sophisticated Learning Implementations: MATLAB and Python code for the "Sophisticated Learning" algorithm from Hodson et al.'s research on model-based planning.
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Updated
May 28, 2024 - Jupyter Notebook
Sophisticated Learning Implementations: MATLAB and Python code for the "Sophisticated Learning" algorithm from Hodson et al.'s research on model-based planning.
PyHGF: A neural network library for predictive coding
Expected free energy minimization with approximations to nonlinear observation functions
Personal website of Leo D'Amato
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.
Active Inference & Category Theory
Implementation of the paper "A neural active inference model of perceptual-motor learning" published on Computational Neuroscience in 2023.
Implementation/simulation of active neural generative coding (ANGC) for training neurobiologically-plausible active inference agent models.
Code, figures, animations for a NARX-EFE based agent.
[NeurIPS 2021] Contrastive learning formulation of the active inference framework, for matching visual goal states.
Minimal model of tool discovery and tool innovation using active inference
Multi-Agent Robot Learning algorithm using Deep Active Inference (DAI) for road hazard anomaly detection and Soft Actor Critic decomposed for multi-agent settings (mSAC)
An active inference agent based on expected free energy minimization with a nonlinear autoregressive exogenous model.
Application of active inference to reinforcement learning.
Deep Active Inference of Mountain Car Problem
Archive of active inference agents based on reactive message passing.
DIE — is an Artificial Life project aimed at reproducing emergence of distributed intelligence under environmental pressures using learning cellular automata models.
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