Curriculum

At Shatranj.AI, our curriculum uniquely intertwines the rich heritage of historical strategic board games with the forefront of artificial intelligence (AI) innovation. Designed to span the breadth of time from the dawn of civilization to the cutting edge of technology, this program equips students with a profound understanding and skills that honor our past while navigating the future.

Curriculum Overview

1. Historic Mind Games Across Civilizations: Our educational odyssey begins with a deep dive into the historic mind games that have shaped European, Mediterranean, African, and Asian civilizations. This segment aims to instill an appreciation for the diverse strategic games that have facilitated intellectual and cultural exchanges throughout human history, including chess, checkers, and more.

2. Introduction to Python Programming: Students embark on a coding journey starting with the basics of Python programming and progressing through a series of three increasingly complex modules. This foundational programming knowledge is crucial for engaging with AI and developing game simulations.

3. Programming Historic Board Games: This module tasks students with applying their burgeoning coding skills to recreate classic board games such as 3-stone, 9-stone, Mankala, the Ur game, and Checkers, in addition to the intricate strategies of Qirkat and Shatranj. It bridges the ancient with the digital, encouraging innovation and a deeper connection to historical game strategies.

4. Advanced AI and Game Strategy: Further exploration into AI is segmented into three specialized sub-sections:

a) Classical Adversarial Search Algorithms: Covering foundational AI strategies like Minimax and AlphaBeta algorithms, this section introduces students to the competitive and strategic decision-making capabilities of AI in gaming.

b) Solving Puzzles in Historical Board Games: Students apply AI to decode complex puzzles within traditional board games, enhancing their analytical skills and understanding of AI’s strategic applications.

c) Reinforcement Learning: This introduces the concept of reinforcement learning, where algorithms learn optimal actions through rewards, refining AI decision-making processes in gaming scenarios.

5. Evolution of Chess Software: A detailed exploration into the development of chess AI, divided into individual lessons on landmark systems:

a) The Turk: Delving into the history of the Turk, examining its role as an early form of mechanical chess player and its impact on the perception of machine intelligence.

b) DeepBlue: A focused study on DeepBlue, the first computer system to win a chess game and a match against a reigning world champion under standard chess tournament conditions, marking a pivotal moment in AI development.

c) AlphaZero: An in-depth look at AlphaZero, exploring its groundbreaking self-learning capabilities that led it to excel in chess, showcasing the potential of AI to innovate beyond human strategies.

d) Stockfish: A lesson dedicated to Stockfish, detailing its evolution as one of the strongest open-source chess engines, known for its exceptional depth of play and strategic prowess.

6. Ethics and Environmental Impact of AI: Our curriculum concludes with a critical examination of the ethical considerations and environmental impacts of AI advancements. This section encourages thoughtful consideration of AI’s role in society and its potential effects on our ecological footprint.

Join Our Learning Expedition

Shatranj.AI invites students to embark on an extraordinary journey that marries the strategic complexity of ancient board games with the innovative power of AI. Our curriculum is not just a series of lessons but a pathway to discovery, where students gain the skills and insights needed to navigate both the history and the future of technology. Together, we explore the depths of human intellect and creativity, poised at the intersection of tradition and technological breakthrough.