https://github.com/kunalpisolkar24/ai_lab

Collection of practical codes for Savitribai Phule Pune University's Artificial Intelligence (310258) .
https://github.com/kunalpisolkar24/ai_lab

a-star-algorithm ai-algorithms aritificial-intelligence backtracking chatbot graph-traversal greedy-algorithms heuristic-search natural-language-processing search-algorithms sppu-computer-engineering

Last synced: 8 months ago
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Collection of practical codes for Savitribai Phule Pune University's Artificial Intelligence (310258) .

• Host: GitHub
• URL: https://github.com/kunalpisolkar24/ai_lab
• Owner: kunalPisolkar24
• License: mit
• Created: 2024-04-01T13:10:00.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2024-06-22T12:06:33.000Z (over 1 year ago)
• Last Synced: 2025-01-16T05:28:17.306Z (10 months ago)
• Topics: a-star-algorithm, ai-algorithms, aritificial-intelligence, backtracking, chatbot, graph-traversal, greedy-algorithms, heuristic-search, natural-language-processing, search-algorithms, sppu-computer-engineering
• Language: Java
• Homepage:
• Size: 133 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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README

          
##  🧠 Artificial Intelligence Laboratory - Savitribai Phule Pune University 🧠

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This repository contains practical implementations for the Artificial Intelligence component of the **Laboratory Practice II (310258)** course offered in the Third Year of Computer Engineering (2019 Course) at Savitribai Phule Pune University.  Explore the world of intelligent agents, search algorithms, and AI applications! 

🏛️ **Course Information:**

* **University:** Savitribai Phule Pune University

* **Course Name:** Laboratory Practice II (310258)

* **Focus:** Artificial Intelligence

* **Companion Courses:** 

    * Artificial Intelligence (310253)

    * Elective II (310254) 

* **Credit:** 02

* **Examination Scheme:**

    * Practical: 04 Hours/Week

    * Term Work: 50 Marks

    * Practical Exam: 25 Marks

🎯 **Learning Objectives:**

* Gain a deep understanding of search strategies used in AI, including informed, uninformed, and heuristic approaches.

* Apply fundamental AI principles to design solutions for problems involving:

    * Problem-solving

    * Inference

    * Perception 

    * Knowledge representation

    * Machine learning 

* Design, develop, and implement interactive AI applications.

💡 **Course Outcomes (Artificial Intelligence):**

Upon completion of this laboratory component, students will be able to:

* **CO1:** Design intelligent systems leveraging different informed/uninformed search and heuristic algorithms.

* **CO2:** Apply core AI principles in crafting solutions that require problem-solving, inference, perception, knowledge representation, and learning capabilities.

* **CO3:** Design and develop interactive AI applications.

📂 **Practical Implementations:**

| Practical No. | Description |

|---|---|

| 1 | Implement Depth-First Search (DFS) and Breadth-First Search (BFS) algorithms. Use an undirected graph and develop a recursive algorithm to search all vertices within a graph or tree data structure. |

| 2 | Implement the A* Search algorithm to solve a game search problem.  |

| 3 | Implement the Greedy Search algorithm for one of the following applications:  |

|   |  I) Selection Sort |

|   |  II) Minimum Spanning Tree |

|   |  III) Single-Source Shortest Path Problem |

|   |  IV) Job Scheduling Problem |

|   |  V) Prim's Minimal Spanning Tree Algorithm |

|   |  VI) Kruskal's Minimal Spanning Tree Algorithm |

|   |  VII) Dijkstra's Minimal Spanning Tree Algorithm | 

| 4 | Implement a solution for a Constraint Satisfaction Problem using Branch and Bound and Backtracking techniques for the N-Queens problem or a graph coloring problem. |

| 5 | Develop a basic chatbot for a suitable customer interaction application. |

| 6 | Implement one of the following Expert Systems: |

|   |  I) Information Management System |

|   |  II) Hospital and Medical Facility System |

|   |  III) Help Desk Management System |

|   |  IV) Employee Performance Evaluation System |

|   |  V) Stock Market Trading System |

|   |  VI) Airline Scheduling and Cargo Scheduling System |

🚀 **Getting Started:**

Navigate to the directory of the AI practical implementation you want to explore. Each directory contains well-documented code files with clear instructions to guide your learning.

🙌 **Contributions:**

We encourage contributions, enhancements, and feedback from the AI and programming communities! If you have improvements, bug fixes, or additional practical examples to share, please open a pull request. Refer to our [CONTRIBUTING.md](./CONTRIBUTING.md) file for guidelines.

📄 **License:**

This repository is distributed under the [MIT License](./LICENSE), allowing you to use, modify, and distribute the code for educational and personal projects. 

Let's learn and build intelligent systems together! 🚀