Deterministic LLMs Outputs for AI Applications and AI Agents

Experimental Python implementation of the Clarion cognitive architecture

Bayesian Parameter Estimation (based on pystan) of reinforcement learning and sequential sampling models, and combinations of the two.

Predictive human performance modeling for UI/UX design

Metacognitive efficiency modelling in Python.

The code of COMMA: Modeling Relationship among Motivations, Emotions and Actions in Language-based Human Activities. https://aclanthology.org/2022.coling-1.15.pdf In COLING 2022.

This repository contains the collection of Cognitive Science computation modeling projects made for the DTU Human-Centered AI course 02458: Cognitive Modeling

Teaching materials for BayesCog workshop, UKE Hamburg (Part 2).

spatial_attenNCM (Spatial Attention Neuro-Cognitive Modeling) used some hierarchical neuro-cognitive models to find out the spatial attention effect on perceptual decision making.

A set of tutorials for building likelihood based models in ACT-R

Artificial Intelligence for the study of emerging symbol-based communication in artificial creatures.

Cognitive Service Composition. COPERNIC stands for COgnitively-inspired Pervasive middlEware for emeRgeNt ServIce Composition. This framework allows you to perform service composition using distributed services on a pervasive computing environment with multiple devices.

CogniBench is a software framework for benchmarking cognitive models

The ARCADIA framework is for developing integrated, intelligent systems. This distribution includes several models and the components, sensors, etc. required to run them.

Balsamiq Wireframes to CogTool conversion.

Models of Motor Inhibition during Motor Imagery

PyTorch implementation of Feature Extracting Bidirectional Associative Memory (FEBAM).

Portfolio assignments from the Advanced Cognitive Modelling Course at the Master of Cognitive Science at AU

The repository for the SNU course on the fundamentals and applications of cognitive modeling in fall, 2018.