adjust sat solver to new files
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@ -233,6 +233,10 @@ class GameState():
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def hand_size(self):
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return self.instance.hand_size
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@property
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def deck_size(self):
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return self.instance.deck_size
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# Properties of GameState
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218
sat.py
218
sat.py
@ -4,12 +4,9 @@ import json
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from typing import List
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from concurrent.futures import ProcessPoolExecutor
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from compress import DeckCard, Action, ActionType, link, decompress_deck
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from greedy_solver import GameState, GreedyStrategy
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COLORS = 'rygbp'
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STANDARD_HAND_SIZE = {2: 5, 3: 5, 4: 4, 5: 4, 6: 3}
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NUM_STRIKES_TO_LOSE = 3
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from hanabi import DeckCard, Action, ActionType, GameState, HanabiInstance
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from compress import link, decompress_deck
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from greedy_solver import GreedyStrategy
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# literals to model game as sat instance to check for feasibility
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@ -17,33 +14,7 @@ NUM_STRIKES_TO_LOSE = 3
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class Literals():
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# num_suits is total number of suits, i.e. also counts the dark suits
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# default distribution among all suits is assumed
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def __init__(self, num_players, num_suits, num_dark_suits=0):
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assert ( 2 <= num_players <= 6 )
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## some game parameters
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self.num_players = num_players
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self.num_suits = num_suits
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self.num_dark_suits = num_dark_suits
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self.hand_size = STANDARD_HAND_SIZE[num_players]
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self.num_strikes = NUM_STRIKES_TO_LOSE
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self.deck_size = 10 * num_suits - 5 * num_dark_suits
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self.distributed_cards = self.num_players * self.hand_size
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self.draw_pile_size = self.deck_size - self.distributed_cards
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## maximum number of moves in any game that can achieve max score
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# each suit gives 15 moves, as we can play and discard 5 cards each and give 5 clues. dark suits only give 5 moves, since no discards are added
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# number of cards that remain in players hands after end of game. they cost 2 turns each, since we cannot discard them and also have one clue less
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# 8 clues at beginning, one further clue for each suit but one (the clue of the last 5 is never useful since it is gained in the extra-round)
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# subtract a further move for a second 5-clue that can't be used in 5 or 6-player games, since the extraround starts too soon
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self.max_moves = 15 * num_suits - 10 * num_dark_suits \
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- 2 * num_players * (self.hand_size - 1) \
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+ 8 + (num_suits - 1) \
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+ (-1 if num_players >= 5 else 0)
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###
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# note that we generate 'literals' always one out of boundary and set them to explicit truth values. This makes sat formulation easier but has no actual overhead in solving it
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# move are numbered starting with 0
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def __init__(self, instance: HanabiInstance):
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# clues[m][i] == "after move m we have at least i clues"
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self.clues = {
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@ -54,20 +25,20 @@ class Literals():
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**{ i: Symbol('m{}clues{}'.format(m, i)) for i in range(1, 9) },
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9: Bool(False) # never 9 or more clues. This will implicitly forbid discarding at 8 clues later
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}
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for m in range(self.max_moves)
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for m in range(instance.max_winning_moves)
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}
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}
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# strikes[m][i] == "after move m we have at least i strikes"
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self.strikes = {
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-1: {i: Bool(i == 0) for i in range(0, self.num_strikes + 1)} # no strikes when we start
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-1: {i: Bool(i == 0) for i in range(0, instance.num_strikes + 1)} # no strikes when we start
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, **{
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m: {
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0: Bool(True),
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**{ s: Symbol('m{}strikes{}'.format(m,s)) for s in range(1, self.num_strikes) },
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self.num_strikes: Bool(False) # never so many clues that we lose. Implicitly forbids striking out
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**{ s: Symbol('m{}strikes{}'.format(m,s)) for s in range(1, instance.num_strikes) },
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instance.num_strikes: Bool(False) # never so many clues that we lose. Implicitly forbids striking out
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}
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for m in range(self.max_moves)
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for m in range(instance.max_winning_moves)
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}
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}
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@ -75,8 +46,8 @@ class Literals():
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self.extraround = {
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-1: Bool(False)
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, **{
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m: Bool(False) if m < self.draw_pile_size else Symbol('m{}extra'.format(m)) # it takes at least as many turns as cards in the draw pile to start the extra round
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for m in range(0, self.max_moves)
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m: Bool(False) if m < instance.draw_pile_size else Symbol('m{}extra'.format(m)) # it takes at least as many turns as cards in the draw pile to start the extra round
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for m in range(0, instance.max_winning_moves)
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}
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}
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@ -84,26 +55,26 @@ class Literals():
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self.dummyturn = {
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-1: Bool(False)
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, **{
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m: Bool(False) if m < self.draw_pile_size + self.num_players else Symbol('m{}dummy'.format(m))
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for m in range(0, self.max_moves)
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m: Bool(False) if m < instance.draw_pile_size + instance.num_players else Symbol('m{}dummy'.format(m))
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for m in range(0, instance.max_winning_moves)
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}
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}
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# draw[m][i] == "at move m we play/discard deck[i]"
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self.discard = {
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m: {i: Symbol('m{}discard{}'.format(m, i)) for i in range(self.deck_size)}
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for m in range(self.max_moves)
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m: {i: Symbol('m{}discard{}'.format(m, i)) for i in range(instance.deck_size)}
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for m in range(instance.max_winning_moves)
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}
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# draw[m][i] == "at move m we draw deck card i"
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self.draw = {
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-1: { i: Bool(i == self.distributed_cards - 1) for i in range(self.distributed_cards - 1, self.deck_size) }
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-1: { i: Bool(i == instance.num_dealt_cards - 1) for i in range(instance.num_dealt_cards - 1, instance.deck_size) }
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, **{
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m: {
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self.distributed_cards - 1: Bool(False),
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**{i: Symbol('m{}draw{}'.format(m, i)) for i in range(self.distributed_cards, self.deck_size)}
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instance.num_dealt_cards - 1: Bool(False),
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**{i: Symbol('m{}draw{}'.format(m, i)) for i in range(instance.num_dealt_cards, instance.deck_size)}
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}
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for m in range(self.max_moves)
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for m in range(instance.max_winning_moves)
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}
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}
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@ -112,82 +83,89 @@ class Literals():
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-1: Bool(False)
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, **{
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m: Symbol('m{}newstrike'.format(m))
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for m in range(self.max_moves)
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for m in range(instance.max_winning_moves)
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}
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}
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# progress[m][card = (suitIndex, rank)] == "after move m we have played in suitIndex up to rank"
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self.progress = {
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-1: {(s, r): Bool(r == 0) for s in range(0, self.num_suits) for r in range(0, 6)} # at start, have only played rank zero
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-1: {(s, r): Bool(r == 0) for s in range(0, instance.num_suits) for r in range(0, 6)} # at start, have only played rank zero
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, **{
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m: {
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**{(s, 0): Bool(True) for s in range(0, self.num_suits)},
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**{(s, r): Symbol('m{}progress{}{}'.format(m, s, r)) for s in range(0, self.num_suits) for r in range(1, 6)}
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**{(s, 0): Bool(True) for s in range(0, instance.num_suits)},
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**{(s, r): Symbol('m{}progress{}{}'.format(m, s, r)) for s in range(0, instance.num_suits) for r in range(1, 6)}
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}
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for m in range(self.max_moves)
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for m in range(instance.max_winning_moves)
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}
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}
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## Utility variables
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# discard_any[m] == "at move m we play/discard a card"
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self.discard_any = { m: Symbol('m{}discard_any'.format(m)) for m in range(self.max_moves) }
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self.discard_any = { m: Symbol('m{}discard_any'.format(m)) for m in range(instance.max_winning_moves) }
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# draw_any[m] == "at move m we draw a card"
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self.draw_any = {m: Symbol('m{}draw_any'.format(m)) for m in range(self.max_moves)}
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self.draw_any = {m: Symbol('m{}draw_any'.format(m)) for m in range(instance.max_winning_moves)}
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# play[m] == "at move m we play a card"
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self.play = {m: Symbol('m{}play'.format(m)) for m in range(self.max_moves)}
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self.play = {m: Symbol('m{}play'.format(m)) for m in range(instance.max_winning_moves)}
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# play5[m] == "at move m we play a 5"
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self.play5 = {m: Symbol('m{}play5'.format(m)) for m in range(self.max_moves)}
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self.play5 = {m: Symbol('m{}play5'.format(m)) for m in range(instance.max_winning_moves)}
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# incr_clues[m] == "at move m we obtain a clue"
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self.incr_clues = {m: Symbol('m{}c+'.format(m)) for m in range(self.max_moves)}
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self.incr_clues = {m: Symbol('m{}c+'.format(m)) for m in range(instance.max_winning_moves)}
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def solve_sat(game_state: GameState):
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ls = Literals(game_state.num_players, game_state.num_suits, game_state.num_dark_suits)
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def solve_sat(starting_state: GameState | HanabiInstance):
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if isinstance(starting_state, HanabiInstance):
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instance = starting_state
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game_state = GameState(instance)
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elif isinstance(starting_state, GameState):
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instance = starting_state.instance
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game_state = starting_state
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else:
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raise ValueError("Bad argument type")
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ls = Literals(instance)
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##### setup of initial game state
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# properties used later to model valid moves
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num_dark_suits = game_state.num_dark_suits
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num_suits = game_state.num_suits
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deck = game_state.deck
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next_draw = game_state.progress
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starting_hands = [[card.deck_index for card in hand] for hand in game_state.hands]
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first_turn = len(game_state.actions)
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# set initial clues
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for i in range(0,10):
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ls.clues[first_turn - 1][i] = Bool(i <= game_state.clues)
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if isinstance(starting_state, GameState):
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# have to set additional variables
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# set initial strikes
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for i in range(0, game_state.num_strikes + 1):
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ls.strikes[first_turn - 1][i] = Bool(i <= game_state.strikes)
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# set initial clues
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for i in range(0,10):
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ls.clues[first_turn - 1][i] = Bool(i <= game_state.clues)
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# check if extraround has started (usually not)
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ls.extraround[first_turn - 1] = Bool(game_state.remaining_extra_turns < game_state.num_players)
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ls.dummyturn[first_turn -1] = Bool(False)
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# set recent draws: important to model progress
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# we just pretend that the last card drawn was in fact drawn last turn,
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# regardless of when it was actually drawn
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for neg_turn in range(1, min(9, first_turn + 2)):
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for i in range(game_state.num_players * game_state.hand_size, game_state.deck_size):
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ls.draw[first_turn - neg_turn][i] = Bool(neg_turn == 1 and i == game_state.progress - 1)
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# forbid re-drawing of the last card drawn
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for m in range(first_turn, ls.max_moves):
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ls.draw[m][game_state.progress - 1] = Bool(False)
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# set initial strikes
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for i in range(0, instance.num_strikes + 1):
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ls.strikes[first_turn - 1][i] = Bool(i <= game_state.strikes)
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# check if extraround has started (usually not)
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ls.extraround[first_turn - 1] = Bool(game_state.remaining_extra_turns < game_state.num_players)
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ls.dummyturn[first_turn -1] = Bool(False)
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# set recent draws: important to model progress
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# we just pretend that the last card drawn was in fact drawn last turn,
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# regardless of when it was actually drawn
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for neg_turn in range(1, min(9, first_turn + 2)):
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for i in range(instance.num_players * instance.hand_size, instance.deck_size):
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ls.draw[first_turn - neg_turn][i] = Bool(neg_turn == 1 and i == game_state.progress - 1)
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# forbid re-drawing of the last card drawn
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for m in range(first_turn, instance.max_winning_moves):
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ls.draw[m][game_state.progress - 1] = Bool(False)
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# model initial progress
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for s in range(0, game_state.num_suits):
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for r in range(0, 6):
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ls.progress[first_turn - 1][s, r] = Bool(r <= game_state.stacks[s])
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# model initial progress
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for s in range(0, game_state.num_suits):
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for r in range(0, 6):
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ls.progress[first_turn - 1][s, r] = Bool(r <= game_state.stacks[s])
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### Now, model all valid moves
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@ -196,10 +174,10 @@ def solve_sat(game_state: GameState):
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Implies(ls.dummyturn[m], Not(ls.discard_any[m])),
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# definition of discard_any
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Iff(ls.discard_any[m], Or(ls.discard[m][i] for i in range(ls.deck_size))),
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Iff(ls.discard_any[m], Or(ls.discard[m][i] for i in range(instance.deck_size))),
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# definition of draw_any
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Iff(ls.draw_any[m], Or(ls.draw[m][i] for i in range(next_draw, ls.deck_size))),
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Iff(ls.draw_any[m], Or(ls.draw[m][i] for i in range(game_state.progress, instance.deck_size))),
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# ls.draw implies ls.discard (and converse true before the ls.extraround)
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Implies(ls.draw_any[m], ls.discard_any[m]),
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@ -209,7 +187,7 @@ def solve_sat(game_state: GameState):
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Implies(ls.play[m], ls.discard_any[m]),
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# definition of ls.play5
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Iff(ls.play5[m], And(ls.play[m], Or(ls.discard[m][i] for i in range(ls.deck_size) if deck[i].rank == 5))),
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Iff(ls.play5[m], And(ls.play[m], Or(ls.discard[m][i] for i in range(instance.deck_size) if instance.deck[i].rank == 5))),
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# definition of ls.incr_clues
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Iff(ls.incr_clues[m], And(ls.discard_any[m], Implies(ls.play[m], And(ls.play5[m], Not(ls.clues[m-1][8]))))),
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@ -225,38 +203,38 @@ def solve_sat(game_state: GameState):
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Iff(ls.strike[m], And(ls.discard_any[m], Not(ls.play[m]), ls.clues[m-1][8])),
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# change of strikes
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*[Iff(ls.strikes[m][i], Or(ls.strikes[m-1][i], And(ls.strikes[m-1][i-1], ls.strike[m]))) for i in range(1, ls.num_strikes + 1)],
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*[Iff(ls.strikes[m][i], Or(ls.strikes[m-1][i], And(ls.strikes[m-1][i-1], ls.strike[m]))) for i in range(1, instance.num_strikes + 1)],
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# less than 0 clues not allowed
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Implies(Not(ls.discard_any[m]), Or(ls.clues[m-1][1], ls.dummyturn[m])),
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# we can only draw card i if the last ls.drawn card was i-1
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*[Implies(ls.draw[m][i], Or(And(ls.draw[m0][i-1], *[Not(ls.draw_any[m1]) for m1 in range(m0+1, m)]) for m0 in range(max(first_turn - 1, m-9), m))) for i in range(next_draw, ls.deck_size)],
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*[Implies(ls.draw[m][i], Or(And(ls.draw[m0][i-1], *[Not(ls.draw_any[m1]) for m1 in range(m0+1, m)]) for m0 in range(max(first_turn - 1, m-9), m))) for i in range(game_state.progress, instance.deck_size)],
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# we can only draw at most one card (NOTE: redundant, FIXME: avoid quadratic formula)
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AtMostOne(ls.draw[m][i] for i in range(next_draw, ls.deck_size)),
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AtMostOne(ls.draw[m][i] for i in range(game_state.progress, instance.deck_size)),
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# we can only discard a card if we drew it earlier...
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*[Implies(ls.discard[m][i], Or(ls.draw[m0][i] for m0 in range(m-ls.num_players, first_turn - 1, -ls.num_players))) for i in range(next_draw, ls.deck_size)],
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*[Implies(ls.discard[m][i], Or(ls.draw[m0][i] for m0 in range(m-instance.num_players, first_turn - 1, -instance.num_players))) for i in range(game_state.progress, instance.deck_size)],
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# ...or if it was part of the initial hand
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*[Not(ls.discard[m][i]) for i in range(0, next_draw) if i not in starting_hands[m % ls.num_players] ],
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*[Not(ls.discard[m][i]) for i in range(0, game_state.progress) if i not in starting_hands[m % instance.num_players] ],
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# we can only discard a card if we did not discard it yet
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*[Implies(ls.discard[m][i], And(Not(ls.discard[m0][i]) for m0 in range(m-ls.num_players, first_turn - 1, -ls.num_players))) for i in range(ls.deck_size)],
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*[Implies(ls.discard[m][i], And(Not(ls.discard[m0][i]) for m0 in range(m-instance.num_players, first_turn - 1, -instance.num_players))) for i in range(instance.deck_size)],
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# we can only discard at most one card (FIXME: avoid quadratic formula)
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AtMostOne(ls.discard[m][i] for i in range(ls.deck_size)),
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AtMostOne(ls.discard[m][i] for i in range(instance.deck_size)),
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# we can only play a card if it matches the progress
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*[Implies(
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And(ls.discard[m][i], ls.play[m]),
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And(
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Not(ls.progress[m-1][deck[i].suitIndex, deck[i].rank]),
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ls.progress[m-1][deck[i].suitIndex, deck[i].rank-1 ]
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Not(ls.progress[m-1][instance.deck[i].suitIndex, instance.deck[i].rank]),
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ls.progress[m-1][instance.deck[i].suitIndex, instance.deck[i].rank-1 ]
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)
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)
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for i in range(ls.deck_size)
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for i in range(instance.deck_size)
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],
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# change of progress
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@ -266,46 +244,46 @@ def solve_sat(game_state: GameState):
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Or(
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ls.progress[m-1][s, r],
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And(ls.play[m], Or(ls.discard[m][i]
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for i in range(0, ls.deck_size)
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if deck[i] == DeckCard(s, r) ))
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for i in range(0, instance.deck_size)
|
||||
if instance.deck[i] == DeckCard(s, r) ))
|
||||
)
|
||||
)
|
||||
for s in range(0, ls.num_suits)
|
||||
for s in range(0, instance.num_suits)
|
||||
for r in range(1, 6)
|
||||
],
|
||||
|
||||
# extra round bool
|
||||
Iff(ls.extraround[m], Or(ls.extraround[m-1], ls.draw[m-1][ls.deck_size-1])),
|
||||
Iff(ls.extraround[m], Or(ls.extraround[m-1], ls.draw[m-1][instance.deck_size-1])),
|
||||
|
||||
# dummy turn bool
|
||||
*[Iff(ls.dummyturn[m], Or(ls.dummyturn[m-1], ls.draw[m-1 - ls.num_players][ls.deck_size-1])) for i in range(0,1) if m >= ls.num_players]
|
||||
*[Iff(ls.dummyturn[m], Or(ls.dummyturn[m-1], ls.draw[m-1 - instance.num_players][instance.deck_size-1])) for i in range(0,1) if m >= instance.num_players]
|
||||
)
|
||||
|
||||
win = And(
|
||||
# maximum progress at each color
|
||||
*[ls.progress[ls.max_moves-1][s, 5] for s in range(0, ls.num_suits)],
|
||||
*[ls.progress[instance.max_winning_moves-1][s, 5] for s in range(0, instance.num_suits)],
|
||||
|
||||
# played every color/value combination (NOTE: redundant, but makes solving faster)
|
||||
*[
|
||||
Or(
|
||||
And(ls.discard[m][i], ls.play[m])
|
||||
for m in range(first_turn, ls.max_moves)
|
||||
for i in range(ls.deck_size)
|
||||
for m in range(first_turn, instance.max_winning_moves)
|
||||
for i in range(instance.deck_size)
|
||||
if game_state.deck[i] == DeckCard(s, r)
|
||||
)
|
||||
for s in range(0, ls.num_suits)
|
||||
for s in range(0, instance.num_suits)
|
||||
for r in range(1, 6)
|
||||
if r > game_state.stacks[s]
|
||||
]
|
||||
)
|
||||
|
||||
constraints = And(*[valid_move(m) for m in range(first_turn, ls.max_moves)], win)
|
||||
constraints = And(*[valid_move(m) for m in range(first_turn, instance.max_winning_moves)], win)
|
||||
# print('Solving instance with {} variables, {} nodes'.format(len(get_atoms(constraints)), get_formula_size(constraints)))
|
||||
|
||||
model = get_model(constraints)
|
||||
if model:
|
||||
# print_model(model, game_state, ls)
|
||||
solution = toJSON(model, game_state, ls)
|
||||
solution = evaluate_model(model, game_state, ls)
|
||||
return True, solution
|
||||
else:
|
||||
#conj = list(conjunctive_partition(constraints))
|
||||
@ -316,6 +294,7 @@ def solve_sat(game_state: GameState):
|
||||
# print(f.serialize())
|
||||
return False, None
|
||||
|
||||
|
||||
def print_model(model, cur_game_state, ls: Literals):
|
||||
deck = cur_game_state.deck
|
||||
for m in range(ls.max_moves):
|
||||
@ -330,12 +309,15 @@ def print_model(model, cur_game_state, ls: Literals):
|
||||
print(', '.join(f for f in flags if model.get_py_value(getattr(ls, f)[m])))
|
||||
|
||||
|
||||
def toJSON(model, cur_game_state: GameState, ls: Literals) -> GameState:
|
||||
for m in range(len(cur_game_state.actions), ls.max_moves):
|
||||
|
||||
# given the initial game state and the model found by the SAT solver,
|
||||
# evaluates the model to produce a full game history
|
||||
def evaluate_model(model, cur_game_state: GameState, ls: Literals) -> GameState:
|
||||
for m in range(len(cur_game_state.actions), cur_game_state.instance.max_winning_moves):
|
||||
if model.get_py_value(ls.dummyturn[m]):
|
||||
break
|
||||
if model.get_py_value(ls.discard_any[m]):
|
||||
card_idx = next(i for i in range(0, ls.deck_size) if model.get_py_value(ls.discard[m][i]))
|
||||
card_idx = next(i for i in range(0, cur_game_state.instance.deck_size) if model.get_py_value(ls.discard[m][i]))
|
||||
if model.get_py_value(ls.play[m]) or model.get_py_value(ls.strike[m]):
|
||||
cur_game_state.play(card_idx)
|
||||
else:
|
||||
@ -345,6 +327,8 @@ def toJSON(model, cur_game_state: GameState, ls: Literals) -> GameState:
|
||||
|
||||
return cur_game_state
|
||||
|
||||
|
||||
|
||||
def run_deck():
|
||||
puzzle = False
|
||||
if puzzle:
|
||||
@ -361,7 +345,7 @@ def run_deck():
|
||||
|
||||
print(deck)
|
||||
|
||||
gs = GameState(num_p, deck)
|
||||
gs = GameState(HanabiInstance(deck, num_p))
|
||||
if puzzle:
|
||||
gs.play(2)
|
||||
else:
|
||||
@ -372,7 +356,7 @@ def run_deck():
|
||||
solvable, sol = solve_sat(gs)
|
||||
if solvable:
|
||||
print(sol)
|
||||
print(link(sol.to_json()))
|
||||
print(link(sol))
|
||||
else:
|
||||
print('unsolvable')
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user