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This project explores the creation of dynamic agent-based environments using the Environment Editor (EE), a custom-built tool designed to generate multi-layered grid systems for simulations and games.

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๐ŸŒ๐Ÿš€ Welcome to LAB 1: Agent Adventure! ๐Ÿ•น๏ธ๐Ÿค–

๐Ÿง‘โ€๐ŸŽ“ Student Name: Donfack Tsopfack Yves Dylane

๐ŸŽฎโœจ Step 1: Environment Creation ๐ŸŽจ๐ŸŒฑ

Welcome to the world of EE! ๐Ÿ› ๏ธ EE (Enviroment Editor) is the magical app that I built to create multi-layered grid environments ๐Ÿž๏ธ.

It's where the agent does its thing! Think of it as a playground for the agentโ€”each layer in this world has a unique role.

๐ŸŽฏ Layer Breakdown:

Layer 2 (Roads) ๐Ÿ›ค๏ธ: Paths where the agent can freely roam.

Layer 3 (Target) ๐ŸŽฏ: The ultimate goal for our little agent.

Layer 5 (Agent) ๐Ÿค–: This is where the agent lives, moves, and grooves.

Layer 8 (Obstacles) โ›”: Challenges the agent must overcome.

Decorative Layers ๐ŸŒณ๐Ÿก: Just some visuals to make the world look pretty!

To learn more about EE, check out the repo here! ๐Ÿ˜Ž

https://github.com/yvesdylane/EnviromentEditor

๐Ÿค–โœจ Step 2: Agent Design ๐Ÿ› ๏ธ

Time to meet our Agent! ๐Ÿฆพ Itโ€™s got personality and a bunch of cool properties and methods to help it move, navigate, and explore its world. Here's what makes our agent tick:

Image ๐ŸŽจ: A stylish sprite to represent the agent.

X, Y Coordinates ๐Ÿ“: Where in the grid world it shows up.

Scale ๐Ÿ“: Size it up, size it down, we got this!

Tile Size ๐Ÿ”ณ: This is the pixel magic that helps the agent find its perfect spot on the screen.

But wait, thereโ€™s more! The agent's got some serious skills when it comes to moving, drawing itself, and checking for valid moves. ๐Ÿ•บ๐Ÿ’ฅ

๐Ÿ”„โœจ Step 3: Agent Simulation Loop ๐ŸŒ€

This agent never sleeps! ๐Ÿ›Œ๐Ÿ’ค Every 30 FPS, it updates itself, moving and grooving across the environment in real time! ๐Ÿ•ฐ๏ธโšก

๐Ÿš€โœจ Step 4: Pathfinding Enhancement ๐Ÿ›ค๏ธ๐Ÿ”

Hereโ€™s where things get next-level! ๐Ÿ’ก Weโ€™ve taken pathfinding to new heights with BFS (Breadth-First Search)!

๐Ÿ“šโœจ It helps the agent navigate in the most efficient way possible, finding the shortest path with ease.

๐Ÿ“Š Comparison of Pathfinding Methods:

Feature Original Code Enhanced Code (BFS)

Movement Random choices ๐ŸŽฒ Prioritizes shortest path ๐Ÿš€

Efficiency Some backtracking ๐Ÿ”„ Less backtracking ๐Ÿ”ฅ

Best Use Case Small grids ๐Ÿž๏ธ Complex grids with obstacles ๐Ÿ™๏ธ

The enhanced code reduces random movements, so the agent reaches its goal faster and with fewer detours! ๐Ÿšดโ€โ™‚๏ธ๐Ÿ’จ

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This project explores the creation of dynamic agent-based environments using the Environment Editor (EE), a custom-built tool designed to generate multi-layered grid systems for simulations and games.

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