Briefly explain the work that you did on this project: What code were you given? What code did you create yourself?

I worked on implementing a Deep Q-learning agent for a treasure hunt game, where the AI-controlled pirate learns to find the treasure. The provided code included the environment setup (TreasureMaze.py) and a memory storage system (GameExperience.py) for storing past game states. My task was to complete the Q-learning implementation, which involved designing the neural network model, managing reinforcement learning updates, and fine-tuning the balance between exploration and exploitation for efficient learning.

Connect your learning from throughout this course to the larger field of computer science: What do computer scientists do and why does it matter?

Computer scientists develop algorithms, build intelligent systems, and solve complex problems using data structures, machine learning, and AI techniques. Their work matters because it powers automation, optimizes decision-making, and improves efficiency in industries ranging from healthcare to finance to cybersecurity. In AI, specifically, reinforcement learning allows systems to learn from experience, leading to smarter automation and better problem-solving in real-world scenarios.

How do I approach a problem as a computer scientist?

Problem-solving in computer science requires breaking the problem into smaller parts, analyzing the constraints, and designing an efficient algorithmic solution. In this project, I first understood the environment and how the agent interacts with it. Then, I implemented a step-by-step training process for the AI to learn optimal paths to the treasure. Debugging and iterating on the model based on performance results helped refine the agent’s behavior.

What are my ethical responsibilities to the end user and the organization?

As a computer scientist, I need to ensure that AI models are fair, transparent, and responsible. In reinforcement learning, biased training data or poorly designed reward structures could lead to unintended or unethical behavior. Additionally, when deploying AI, protecting user privacy, ensuring security, and minimizing unintended consequences are crucial. Ethical AI development means prioritizing fairness and accountability while aligning with organizational goals.