Revise README

Expanded README to include project overview, problem description, solution details, project structure, building instructions, and license information.

Author: rednayan

README.md

@@ -1,7 +1,72 @@
-## Quick Start
+# Taxi Cab Problem — Reinforcement Learning
 
-```console
-$ cc -o nob nob.c
-$ ./nob
-$ ./main
+A Q-learning agent that learns to navigate a taxi in a 5×5 grid world, pick up passengers, and drop them at their destination.
+
+**[▶ Live Demo](https://rednayan.github.io/rl-taxi-cab-problem/)**
+
+![Taxi Environment](https://gymnasium.farama.org/_images/taxi.gif)
+
+## The Problem
+
+Based on the classic [Taxi-v3](https://gymnasium.farama.org/environments/toy_text/taxi/) environment. The taxi must:
+
+1. Navigate a 5×5 grid with walls
+2. Pick up a passenger from one of 4 locations (R, G, Y, B)
+3. Drop them off at another location
+4. Do this as efficiently as possible
+
+**Rewards:**
+- +20 for successful drop-off
+- -1 for each step (encourages efficiency)
+- -10 for illegal pickup/drop-off attempts
+
+**State space:** 500 states (5×5 grid × 5 passenger locations × 4 destinations)
+
+**Actions:** 6 (Up, Down, Left, Right, Pickup, Drop)
+
+## The Solution
+
+This project implements **Q-learning**, a model-free reinforcement learning algorithm. The agent learns a Q-table mapping state-action pairs to expected rewards through trial and error.
+
+```
+Q(s,a) ← Q(s,a) + α[r + γ·max(Q(s',a')) - Q(s,a)]
 ```
+
+**Hyperparameters:**
+- Learning rate (α): 0.1
+- Discount factor (γ): 0.99
+- Exploration rate (ε): 0.1
+- Episodes: 5000
+
+After training, the agent learns the optimal policy and consistently solves the task in minimal steps.
+
+## Project Structure
+
+```
+├── main.c          # Training loop, visualization, Q-learning
+├── taxi.c          # Environment logic (step, reset, rewards)
+├── taxi.h          # Environment struct and function declarations
+```
+
+## Building Locally
+
+Requires [raylib](https://www.raylib.com/) for visualization.
+
+- **Linux:** raylib 5.5 is included in the repo — no installation needed.
+
+- **For other systems:** download the source code of [raylib](https://github.com/raysan5/raylib.git) 
+
+```bash
+# manually with gcc
+gcc -o taxi main.c taxi.c -lraylib -lGL -lm -lpthread
+
+# or Using the nob build system
+# update the `nob.c` file with appropiate file path for a `nob` build.
+./nob
+
+
+```
+
+## License
+
+MIT