cognitive-models

An efficient framework for fitting and comparing hierarchical Bayesian cognitive models

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

Recipes for cognitive modeling using Stan [work in progress]

A python-based graphical user interface for Windows users of fast-dm - a diffusion model analysis tool.

Repository for the MSc project "To Err is Human: Designing Correct-by-Construction Driver Assistance Systems using Cognitive Modelling".

Social Reasoner for Socially-Aware Intelligent Conversational Agents

In this project, we design a recurrent neural network to simulate a cognitive model of decision-making called Multi Alternative Decision Field Theory (MDFT). We train this RNN to learn the parameters of MDFT.

In this project, we use the maximum entropy principle in Inverse reinforcement learning to learn soft constraints from demonstrations obtained from an agent interacting with a non-deterministic MDP. In the second part of this project, we implement various strategies (orchestrators) to mix conflicting policies (e.g. pragmatic vs ethical). In one …

Models of Motor Inhibition during Motor Imagery

Repository of dataset, R Markdown Notebook with codes, and other ancillary materials for a book chapter (👇) on the conceptualisation of ANGER in Indonesian.

A cognitive model testing API based on the JESS rule engine. It provides a simple and easy to use way to test a cognitive model on a given task,

🧠 AI Prompt 知识库 — 沉淀 Prompt Engineering 认知模型、工作流模板与技术笔记 | A curated knowledge base for AI prompt engineering, cognitive models, and workflows.

"At the nexus of origin and change, I find the pivotal truth."

Experimental open protocol for evidence-based working models of human-AI collaboration.

[CogSci 2016] A Computational Exploration of Problem-Solving Strategies and Gaze Behaviors on the Block Design Task

The repository for the SNU course on Dynamics and Cognitive Models in spring, 2019.

NISSG introduces a computation-free cognitive framework where state sequences emerge from observed facts rather than inference. Implemented via NISSGER (Ensemble Recorder), it achieves core intelligence—recording, chaining, and grounding—through structural reproducibility and sensor mappings alone.

A conceptual framework proposed by Celis to describe AI's insentient weakness, semantic-weight imbalance, and value-trajectory distortion. Public timestamp of authorship. Full manuscript remains private.

This theory proposes a layered perceptual framework that autonomously adjusts sensory interpretation based on environmental feedback. It enables real-time adaptability in agents, allowing flexible interaction between perception, prediction, and response.