Skip to content

A stream-lit interface using DQN based AI agent to intelligently distribute tasks among specified employees.

Notifications You must be signed in to change notification settings

Aditya-1874/AI-Task-Scheduler

Folders and files

NameName
Last commit message
Last commit date

Latest commit

ย 

History

5 Commits
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 
ย 

Repository files navigation

AI Scheduler Agent

This project implements an AI-powered task scheduling agent that assigns tasks to employees based on factors like skill matching, current workload, fatigue, and availability. The system includes an interactive user interface built with Streamlit and can intelligently match tasks using deep learning techniques and natural language processing.


๐Ÿ”ง Features

  • ๐Ÿง  AI-based Task Assignment using DQN (Deep Q-Learning).
  • ๐Ÿ’ฌ NLP Parsing of Task Descriptions to extract requirements.
  • ๐Ÿ‘ท Employee Profiling based on skillsets, availability, and fatigue.
  • ๐Ÿ“Š Real-time Visualization of assignments with Streamlit.
  • โ˜๏ธ Can be deployed via Colab + ngrok for quick demos.

๐Ÿ–ฅ๏ธ Usage (via Google Colab)

  1. Open the notebook AI_Scheduler_Agent.ipynb in Google Colab.
  2. Run the cells to:
    • Install dependencies
    • Launch the Streamlit server
    • Tunnel the port using pyngrok
  3. Access the public URL generated to use the app.

๐Ÿš€ Running Locally

Use the app.py file to run:

pip install -r requirements.txt
python -m spacy download en_core_web_lg
streamlit run app.py

About

A stream-lit interface using DQN based AI agent to intelligently distribute tasks among specified employees.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published