{"id":25271,"date":"2024-01-10T12:48:14","date_gmt":"2024-01-10T11:48:14","guid":{"rendered":"https:\/\/www.codemotion.com\/magazine\/?post_type=video&p=25271"},"modified":"2024-01-10T18:17:35","modified_gmt":"2024-01-10T17:17:35","slug":"is-ai-ready-to-beat-highly-complex-strategy-game","status":"publish","type":"video","link":"https:\/\/www.codemotion.com\/magazine\/video\/is-ai-ready-to-beat-highly-complex-strategy-game\/","title":{"rendered":"Is AI Ready to Beat Highly Complex Strategy Games?"},"content":{"rendered":"\n

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AI and games have always been connected. From the simplicity of tic-tac-toe in the ’50s to the strategic intricacies of modern board games, the world of algorithms has been on an ever-evolving quest to conquer the gaming realm. Picture this: a timeline where each decade unfolds a new chapter, introducing challenges that algorithms, in their relentless pursuit, strive to overcome.<\/p>\n\n\n\n

Back in the ’50s, tic-tac-toe was the proving ground. Algorithms like Minimax <\/a><\/strong>took their baby steps, showcasing the potential to predict outcomes and strategize in a confined space of possibilities. Moving into the late ’90s, chess became the battleground, and Deep Blue’s victory against Garry Kasparov demonstrated how algorithms could adapt to a more complex environment.<\/p>\n\n\n\n

The game changed once again in 2007 with Go, a game notorious for its vast possibilities. Enter AlphaGo and the world witnessed a paradigm shift<\/a>. Rule-based approaches took a backseat, making room for the formidable combination of neural networks and machine learning.<\/p>\n\n\n\n

Now, in the 21st century, our attention turns to a very interesting experiment with an even more complex board experience called Commands and Colors: Ancients<\/strong>, a modern board game that throws conventional algorithms for a loop, where incomplete information, chance elements, and almost infinite possible outcomes for player moves mirror the unpredictability of the real world.<\/p>\n\n\n\n

The strategy to victory? Taking Monte Carlo Tree Search<\/a> further than ever before.<\/p>\n\n\n\n

About the video<\/h2>\n\n\n\n

In the video, Technical Principal @Thoughtworks Italia Matteo Vaccari tackles a super complex strategy game called Command and Color: Ancients<\/a>, showcasing an innovative, yet challenging, approach to creating an AI system that can play and beat a human mind.<\/p>\n\n\n\n

What you’ll learn<\/h2>\n\n\n\n

Introduction to Game-Defeating Algorithms:<\/p>\n\n\n\n