RL-Yaniv

The game of Yaniv implemented as a Gymnasium environment to be used for Reinforcement Learning. Ray RLLib is used for training agents using PPO. ParametricActions are used for action embeddings.

Game

The goal is to win a round by getting to 5 points or less and call Yaniv.

Card Rank	Points Value
Joker	0
Ace	1
2-10	same as card
Face Card	10

• Traditional Imperfect information game
• Non-deterministic
• 2-6 players

Deck

• Deck type (52 card deck, 54 card deck with 2 jokers)
• Open/Closed Deck

Card

• Suit (♠♥♦♣)
• Rank (A23456789TJQK)
• Points
• Cardinality
• Unicode

Events/Moves

Moves that a player can take in a turn

• Call Yaniv
• Throw a card on the pile
• Pickup a card from the top of the deck
• Pickup a card from the top of the pile
• End its turn

Implementation

The game is implemented in pure Python (no dependencies), it is wrapped to a environment encoding

Actions

0: Call Yaniv (if 5 point or lower)
1 - 54: Throw card 
    Spades (A2-10JQK), 
    Hearts (..),
    Diamonds (..),
    Clubs (..),
53: Throw Red Joker
54: Throw Black Joker
55: Pickup card from deck
56: Pickup card from pile
57: End turn

Observations

Box(2, 56) Binary masks

• The player's cards
• Card on top of the pile (1-Hot)