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Results of the Online Tic Tac Toe Contest: A Deep Dive into AI and Learning

The Tic Tac Toe Online Contest, led by Russel Ahmed Apu, showcased intense problem-solving and AI application with 5,016 games played by students. With 3,987 games qualifying for scoring, competition was fierce, and many teams excelled, exceeding expectations. The focus was not only on winning but also on understanding failure and learning from experiences. Our innovative scoring system normalized performances to rank teams fairly, emphasizing the importance of ongoing evolution in AI and learning processes in the realm of game design.

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Results of the Online Tic Tac Toe Contest: A Deep Dive into AI and Learning

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  1. CPSC 335Assignment 5 The Game of TIC TAC TOE Online Contest Results By: Russel Ahmed Apu

  2. Contest Objectives • A flavor of AI and Software evolution • Intense problem solving • Researching methods • What works? • What doesn’t work?

  3. Outcome • 5016 games played by students • 3987 games credited to scoring (after 13th) • Participation was phenomenal • Competition was fierce • Some teams performed exceptionally well • The AI exceeded our expectation • Bravo! … • Losing and learning “what doesn’t work” is equally important! • Evolution is the “KEY” • The learning experience is important, winning/losing doesn’t matter • A losing team’s work is equally appreciated

  4. The Raw Scores

  5. Normalizing the Score • Designed to reflect the fair performance of a team • Rank[i,j] = Sqrt( clamp(raw[i,j]-raw[j,i], 0, 100) ) • Score(p) = Sum(Rank[p,i], i=1..n)

  6. The Ranked Score of teams

  7. Final Score and Team Ranking

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