Built an Emergence Simulator Using Conway’s Game of Life

For Week 10 of Project52, I built an interactive simulator based on Conway’s Game of Life, designed as a six-chapter experience to showcase how structured behaviors — like motion, repetition, reproduction, and even computation — can emerge from simple, rule-based systems. Instead of a freeform sandbox, this project guides users through curated scenarios that reveal key properties of emergent complexity, making it both a technical build and a visual storytelling tool for understanding how logic can evolve into lifelike behavior.

I Built QuickType — A Real-Time Typing Game That Lets You Race a Bot

Quicktype is a real-time typing game that lets users race against a simulated bot while tracking their typing speed and accuracy live. Designed with clean UI, responsive animations, and a lightweight stack (HTML, CSS, and vanilla JavaScript), it features dynamic prompts, error tracking with visual indicators, and a local leaderboard that records your top performances.

DQN vs PPO: Which Reinforcement Learning Algorithm Lands Better?

Using OpenAI Gym’s LunarLander-v3 environment, I trained two AI agents from scratch: one using Deep Q-Networks (DQN), a value-based method that learns which actions lead to maximum reward, and the other using Proximal Policy Optimization (PPO), a policy-gradient method that directly learns optimal behaviors. I tracked their learning curves, reward scores, fuel usage, and even visual behaviors to determine which agent could not only land but do so gracefully, efficiently, and reliably.

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