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On Playing Games without Knowing the Rules

This paper explores the intriguing challenge of teaching machines to play games against educated opponents without prior knowledge of the game rules. Using Tic-Tac-Toe as a case study, we present a novel framework where a machine learns the game's rules and strategies through agent-environment interaction. Implemented in Java under the JAGUAR.EX platform, our approach combines reinforcement learning with Q-learning. We showcase results demonstrating how agents learn more effectively when allowed to interact on their own turns, providing insights into AI game strategy development.

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On Playing Games without Knowing the Rules

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  1. On Playing Games without Knowing the Rules Advisor : Dr. Hsu Presenter : Jia-Hao Yang Author :Denis V. Batalov and B. John Oommen

  2. Outline • Motivation • Objective • Method • Experience • Conclusion

  3. Motivation • We know that one of the interesting areas in AI is to teach machine to play a game against an educated opponent. • But if the machines don’t know the rule of the game?

  4. Objective • This paper will show that the machine will learns the rules of the game, tic-tac-toe, and strategy just as paper’s title say.

  5. Method • To accomplish this goal, we assume that the LM interacts with an environment. • Sense-act-learn procedure • Agent-Environment Interaction Protocol (AEip) • AEip • Because we use JAVA to implement this platform, so we call it JAGUAR

  6. EX Method • AEip specification of Tic-tac-toe • Reinforcement • Doesn’t end the game : -1 • Win & Lose & Tie: + 10 & -10 & +5 • Learning algorithm • Q-learning • Select mathod : If t = 0.1=> P = ∞ (greedy) If t = ∞ => p = 1/j (random)

  7. Experiment • This paper just underscore two set of results • The agents were selecting their actions simultaneously

  8. Experiment • How much faster the agents learn to play when they allowed to make a move on their own turn

  9. Conclusion • In this paper we have specified a novel framework and show how an agent can learn to play a new game without any prior knowledge.

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