Skip to content

AFAgarap/csc613m-dlsu

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Introduction to Intelligent Systems

A Simple Path-Finding Game System and Evaluation of its Performance

Usage

This repository is optimized for UNIX-based systems.

$ git clone https://github.com/afagarap/csc613m-dlsu.git/
$ cd csc613m-dlsu
$ sudo apt-get install figlet

Levels of Rationality

We defined three levels of rationality for the agent to determine its path to the goal node.

  • Random strategy. The agent randomly moves around the environment until it miraculously reaches the goal node.
  • Recursive strategy. The agent randomly moves around the environment while avoiding its visited nodes until it reaches the goal node.
  • Recursive strategy with heuristic. The agent moves around the environment with the guide of the beacon while avoiding its visited nodes until it reaches the goal node.

Table 1. Performance of the agent with different strategies in an 8x8 environment configuration.

Level Moves Rotations Failures
0 18 18 10
1 12 17 14
2 10 14 2

Figure 1. The solution of strategy 0 to the path-finding problem, reaching the goal node in 18 moves after 10 attempts.

Figure 2. The solution of strategy 1 to the path-finding problem, reaching the goal node in 12 moves after 14 attempts.

Figure 3. The solution of strategy 2 to the path-finding problem, reaching the goal node in 10 moves after 2 attempts.

Table 2. Performance of the agent with different strategies in a 32x32 environment configuration.

Level Moves Rotations Failures
0 1697 1697 14
1 103 146 784
2 111 172 242

Figure 4. The solution of strategy 0 to the path-finding problem, reaching the goal node in 1697 moves after 14 attempts.

Figure 5. The solution of strategy 1 to the path-finding problem, reaching the goal node in 103 moves after 784 attempts.

Figure 6. The solution of strategy 2 to the path-finding problem, reaching the goal node in 111 moves after 242 attempts.

Table 3. Performance of the agent with different strategies in a 32x32 environment configuration.

Level Moves Rotations Failures
0 1718 1718 1
1 98 148 860
2 56 91 116

Figure 4. The solution of strategy 0 to the path-finding problem, reaching the goal node in 1718 moves after 1 attempt.

Figure 5. The solution of strategy 1 to the path-finding problem, reaching the goal node in 98 moves after 860 attempts.

Figure 6. The solution of strategy 2 to the path-finding problem, reaching the goal node in 56 moves after 116 attempts.

An Enhanced Intelligent System and Evaluation of its Performance

Rule-based Diagnosis System for Skin Diseases

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published