Machine Learning with Python Projects - Rock Paper Scissors

Tell us what’s happening:

Hello fellow players,

I’m seeking your valuable insights and suggestions to improve my performance in the game of Rock-Paper-Scissors.

I’m finding it challenging to achieve a minimum 60% win rate (especially with abbey and kris). I would greatly appreciate any advice you can share to help me improve my game. Thank you!

Your code so far

def player(prev_play, opponent_history=[]):
    mapper = {"R": "P", "P": "S", "S": "R"}
    return mapper.get(prev_play, prev_play)

The results so far:

Final results: {'p1': 399, 'p2': 0, 'tie': 600}
Player 1 win rate: 100.0%
Final results: {'p1': 494, 'p2': 487, 'tie': 18}
Player 1 win rate: 50.35677879714577%
Final results: {'p1': 500, 'p2': 499, 'tie': 0}
Player 1 win rate: 50.050050050050054%
Final results: {'p1': 841, 'p2': 158, 'tie': 0}
Player 1 win rate: 84.18418418418419%

Your browser information:

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Challenge Information:

Machine Learning with Python Projects - Rock Paper Scissors

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