A

artificial-intelligence

aGrUM is a C++ library designed for easily building applications using graphical models such as Bayesian networks, influence diagrams, decision trees, GAI networks or Markov decision processes.

[2025] European news intelligence platform with dual-layer AI sentiment analysis. Tracks media narrative shifts across 12 sources using VADER baseline + Gemini nuance, vector embeddings for semantic search, and interactive relationship mapping with real-time trend visualization.

[2025] Autonomous Claude Code plugin with pattern learning and skill auto-selection. Features 27 specialized agents across 4 collaborative groups, quality control automation, and intelligent task execution without human approval at each step.

An MCP server for personal second-brain purposes

The aim of N-Queens Problem is to place N queens on an N x N chessboard, in a way so that no queen is in conflict with the others.

This Python code employs the Depth-First Search (DFS) algorithm to find a path from "Arad" to "Bucharest" in the Romania map. It uses a priority queue, backtracking, and a graph representation. The DFS path is printed at the end. Skills demonstrated include graph traversal, priority queue usage, and DFS algorithm implementation.

The code uses backtracking to solve the Constraint Satisfaction Problem (CSP) of map coloring. It checks if assigning colors to regions follows the constraint that no adjacent regions have the same color. The skills involved include algorithm design for backtracking, recursion, and solving CSP problems. The implementation uses Python.

Implementation of UCS on Romania to find shortest distance from Arad to Bucharest based on best-first search algorithm. It uses a dictionary that stores current city mapped to (parent city, current best distance), and frontier is a priority queue to process nodes containing (node id, current city, priority value).

Hackathon project that uses computer vision to offer a bubble sheet correction platform

This project (PoC for now, and part of Shit Bucket) involves face detection, face recognition and adversarial input to protect avatars

An OpenAI Gym for Shopping Cart Reinforcement Learning.

A very simple example of using RL in real life using servo motors.

Learn to drive an radio-controlled car using only a camera. Uses a DonkeyCar simulation, SAC and a VAE. By Winder Research.

Examples demonstrating Kullback-Leibler divergence.

A simplified version of "Cliffworld" in an OpenAI Gym Environment

AI Tool to provide Graphical view of all prices. It has filters so investors can make use of all 37 filters to check which currency is best to invest in. The tool is a analysis tool and we have added 72 currencies in it

Cunning, sneaky and ruthless snake.

A patch for FF v2.3 to allow steps to be formatted for humans.

Mirror of https://humaidq.ae/projects/ff-format-patch/