https://github.com/haroldeustaquio/artificial-intelligence-unam

This repository contains projects and exercises developed during the Artificial Intelligence course at UNAM. It covers topics such as fuzzy logic, adversarial search algorithms, intelligent agents, and more.
https://github.com/haroldeustaquio/artificial-intelligence-unam

adversarial-search artificial-intelligence fuzzy fuzzy-logic intelligent-agent unam

Last synced: about 1 month ago
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This repository contains projects and exercises developed during the Artificial Intelligence course at UNAM. It covers topics such as fuzzy logic, adversarial search algorithms, intelligent agents, and more.

• Host: GitHub
• URL: https://github.com/haroldeustaquio/artificial-intelligence-unam
• Owner: haroldeustaquio
• License: mit
• Created: 2024-10-22T08:19:40.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-11-07T01:21:57.000Z (about 2 months ago)
• Last Synced: 2024-11-07T01:31:12.198Z (about 2 months ago)
• Topics: adversarial-search, artificial-intelligence, fuzzy, fuzzy-logic, intelligent-agent, unam
• Language: Jupyter Notebook
• Homepage:
• Size: 294 KB
• Stars: 4
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Artificial Intelligence UNAM

This repository contains a collection of implementations related to Artificial Intelligence, developed as part of the UNAM AI course. The included projects address fundamental concepts such as intelligent agents, fuzzy logic, and search and decision-making algorithms in the context of games.

## Content

- **Intelligent Agents**: Contains implementations of intelligent agents of different types:

- **Fuzzy Logic**: A system based on fuzzy logic to evaluate the financial risk of clients who apply for car insurance policies. It evaluates the risk based on the applicant's age and driving percentage.

- **Adversarial Search Algorithms**: Examples of search and decision-making algorithms applied to games, exploring concepts such as adversarial search and real-time decision-making.

## Project Description

### Intelligent Agents

Implementations of different types of agents, each with a particular decision-making strategy:

**SimpleReactiveAgent**:

- `garbage collector`: Simulates an agent that collects waste.

- `smart light`: Controls the on/off of lights based on stimuli.

- `vacuum cleaner`: A vacuum cleaner agent that cleans specific spaces.

- `vending machine`: Distributes products based on stimuli.

**ModelBasedAgent**:

- `traffic management`: An agent that manages traffic flow.

- `vending machine`: Improved version that incorporates internal state for informed decisions.

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### Fuzzy Logic

Fuzzy logic system that assesses financial risk for car insurance customers:

- **Input variables**: Age (Young, Adult, Senior) and Driving Percentage (Low, Medium, High).

- **Fuzzy Rules**: Evaluate combinations of age and experience to determine risk.

- **Defuzzification**: Convert the fuzzy result into a precise value representing the level of risk.

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### Adversarial Search Algorithms

Examples of search algorithms for decision making in adversarial and real-time games:

- **Minimax and Alpha-Beta Pruning**: Adversarial search algorithms applied to zero-sum games such as chess.

- **Real-Time Decision Making**: Algorithms for real-time decisions, suitable for fast-reaction games such as Space Invaders.

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If you have suggestions or would like to contribute, please open an *Issue* or make a *Pull Request*. Your participation is welcome to improve and expand this project.