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We want to explore to what extent approaches or techniques from cognitive neuroscience related to machine learning and symbolic tools to represent knowledge, could help to better formalize human learning as studied in education sciences.
To this end, we are developing a research code for measuring learning analytics during activities with tangible objects and middleware between the major tools and algorithms used in this exploratory action of research.

These libraries include :
   - the preliminary implementation of metrizable symbolic data structure allowing performing symbolic derivations using numerical embedding, in an explicitly (thus easily explainable) way, targeting reinforcement symbolic learning or open-ended creative complex problem-solving,
   - a set of C/C++ routines for basic calculations, with the portions of code executed on connected objects which allow measurement of learning traces, and the control of experiments,
   - C/C ++ or Javascript tools to interface the different software modules used, and a Python wrapper to develop above these functionalities.

Available AIDE modules
GIT repositoryDocumentation
creacogThis project aims to model the learner's cognition and behavior during the CreaCube task.
creaontoOntology specification for a creative problem-solving task, including both a model of the learner and a model of the material used for the task.
creadataThis project aims to analyze CreaCube video annotations.
onto2spaOntology mapping onto a Semantic Pointer Architecture.
symbolingSymbolic data structure numeric grounding
macrovsaMacroscopic implementation of VSA operation

Available AIDE low-level modules API
GIT repositoryDocumentation
aidebuildBuilds multi-language compilation packages and related documentation.
aidesysBasic system C/C++ interfaces to ease multi-language middleware integration.
aidecvImage processing encapsulation via web interface.
aidewebJavascript and C/C++ server side node express utilities for web applications and services.
creaspotAnalysing video of learning activities using machine learning.
esp32gpiocontrolESP32 firmware providing a REST API for controlling the GPIO interface and higher functions:
stepsolverStep by step variational solver mechanism.
tabletopThe Tabletop activites RPi software.
wjsonImplements a JavaScript JSON weak-syntax reader and writer.