Abstract
Big Two is a popular multiplayer card game in Asia. This research proposes a new method, named rule-based AI, for an agent playing Big Two. The novel method derives rules based on the number of cards the AI agent has left and the control position. The rules for two to four cards left are used to select the card combination to discard based on the number of cards remaining in the agent’s hand. The rules for more than four cards left conditionally prioritize discarding the card combination in the classified cards with lower priority. A winning strategy provides guidelines to guarantee that the AI agent will win when a win is achievable within three moves. We also design the rules for the AI agent without control for holding cards and splitting cards. The experimental results show that our proposed AI agent can play Big Two well and outperform randomized AI, conventional AI, and human players, presenting winning rates of 89.60%, 73.00%, and 55.05%, respectively, with the capability of maximizing the winning score and minimizing the number of cards left when the chance of winning is low.
Highlights
Developing an agent for playing a strategy game is crucial [1]
The experimental results show that our artificial intelligence (AI) agent plays well and significantly outperforms every opponent in all the experiments that have been conducted
We performed three experiments to evaluate the performance of our rule-based AI agent
Summary
Developing an agent (artificial player) for playing a strategy game (e.g., chess, mahjong, and Big Two) is crucial [1]. Big Two is a multiplayer card game that is incredibly popular in China and other Asian countries This game has many rule variations, it has one primary aim: each player has 13 cards and tries to discard them all as soon as possible based on valid card combinations. This research proposes a new method, named rule-based AI, for an agent playing Big. Two. Our proposed AI with several rules achieved high winning rates; further research can use this rule-based AI as a baseline player or consider these rules when defining policies for new methods. This AI could potentially be used to give hints to beginners or players hesitating about their turn.
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