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Ajout du travail de la séance.

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80
README.md
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@ -1,8 +1,9 @@
# BUT3 Jeu
Groupe : Dylan LANDRIN, Killian SCHIED
##### Groupe : Dylan LANDRIN, Killian SCHIED
Au cours de cette séance, nous avons implémenté 3 algorythmes en python:
## Séance du 12/09/24
Au cours de cette séance, nous avons implémenté 3 algorithmes en python:
### exploreMax
Le but d'explore max est de déterminer si le joueur 1 peux faire un coup qui mettrais en echec joueur 2.
@ -12,3 +13,78 @@ Le but de Min est l'inverse, il voit s'il peut mettre joueur 1 en échec
### miniMax
miniMax appelle les explorations
## Séance du 17/09/24
Au cours de cette séance, nous avons apportés des modifications dans les fonctions utilisées dans l'algorithme miniMax() ainsi qu'un affichage de l'objet Game.
### exploreMax() et exploreMin()
Des optimisations ont été apportés dans ces fonctions afin de stopper la recherche lorsque une solution a été trouvée.
Exemple :
#### Avant
Test avec 5 allumettes :
```
$ python3 game.py
-----------------------
Game and algorithm data
-----------------------
== Game data ==
Remaining matches : 5
Game state : 0
Actual player : 1
== Algorithm data ==
exploreMax calls = 17
exploreMin calls = 19
First player winning ? = False
```
Test avec 14 allumettes :
```
-----------------------
Game and algorithm data
-----------------------
== Game data ==
Remaining matches : 14
Game state : 0
Actual player : 1
== Algorithm data ==
exploreMax calls = 916
exploreMin calls = 913
First player winning ? = True
```
#### Après
Test avec 5 allumettes :
```
$ python3 game_optimized.py
-----------------------
Game and algorithm data
-----------------------
== Game data ==
Remaining matches : 5
Game state : 0
Actual player : 1
== Algorithm data ==
exploreMax calls = 3
exploreMin calls = 3
First player winning ? = False
```
Test avec 14 allumettes :
```
-----------------------
Game and algorithm data
-----------------------
== Game data ==
Remaining matches : 14
Game state : 0
Actual player : 1
== Algorithm data ==
exploreMax calls = 8
exploreMin calls = 7
First player winning ? = True
```

66
game.py
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class Game(int):
def __init__(self, start):
#Game variables
self.matches = start # number of matches
self.state = 0 #-1 = lost, 0 = draw, +1 = won
self.playerTurn = 1 # 1 = player 1 is playing, 2 = player 2 is playing
#Algorithm variables
self.exploreMaxCalls = 0 # Call counter of exploreMax
self.exploreMinCalls = 0 # Call counter of exploreMax
self.firstPlayerWinning = False # Result of MinMax
def miniMax(self):
'''
`miniMax` function starts the MiniMax algorithm
Params :
self -- the current instance of the game
Return :
-1 = lost or 0 = draw or +1 = won -- depends on the possibility to win of the player
'''
if(self.playerTurn == 1):
res = self.exploreMax(self.matches)
if(self.playerTurn == 2):
res = self.exploreMin(self.matches)
print(res)
if(res == -1):
self.firstPlayerWinning = False
else:
self.firstPlayerWinning = True
return res
def exploreMax(self, n):
'''
`exploreMax` function tries to find if a player has possibilities to win the game
Params :
self -- the current instance of the game
n -- a number of matches
Return :
-1 = lose or 0 = draw or +1 = win -- depends on the possibility to win of the player
'''
self.exploreMaxCalls += 1
bestVal = -1
if(n<=0):
return 1
@ -26,6 +54,17 @@ class Game(int):
return bestVal
def exploreMin(self, n):
'''
`exploreMin` function tries to find if a player has possibilities to win the game
Params :
self -- the current instance of the game
n -- a number of matches
Return :
-1 = lose or 0 = draw or +1 = win -- depends on the possibility to win of the player
'''
self.exploreMinCalls += 1
worstVal = 1
if(n<=0):
return -1
@ -37,6 +76,31 @@ class Game(int):
break
return worstVal
def __str__(self):
'''
`__str__` function overrides the default function to get a custom display when printing the game object
Params :
self -- the current instance of the game
Return :
string -- contains all the game and algorithm values
'''
content = ( "-----------------------\n"
"Game and algorithm data\n"
"-----------------------\n"
"== Game data ==\n"
f"Remaining matches : {self.matches}\n"
f"Game state : {self.state}\n"
f"Actual player : {self.playerTurn}\n"
"== Algorithm data ==\n"
f"exploreMax calls = {self.exploreMaxCalls}\n"
f"exploreMin calls = {self.exploreMinCalls}\n"
f"First player winning ? = {self.firstPlayerWinning}\n"
)
return content
game = Game(5) # Creating Nim game with 5 matches
game.miniMax() # Checking if the player 1 is winning
print(game) # Displays game and algorithm data

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game_optimized.py Normal file
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@ -0,0 +1,119 @@
class Game(int):
def __init__(self, start):
#Game variables
self.matches = start # number of matches
self.state = 0 #-1 = lost, 0 = draw, +1 = won
self.playerTurn = 1 # 1 = player 1 is playing, 2 = player 2 is playing
#Algorithm variables
self.exploreMaxCalls = 0 # Call counter of exploreMax
self.exploreMinCalls = 0 # Call counter of exploreMax
self.firstPlayerWinning = False # Result of MinMax
self.algorithmResFound = False # True if MiniMax algorithm found a result
def miniMax(self):
'''
`miniMax` function starts the MiniMax algorithm
Params :
self -- the current instance of the game
Return :
-1 = lost or 0 = draw or +1 = won -- depends on the possibility to win of the player
'''
self.algorithmResFound = False
if(self.playerTurn == 1):
res = self.exploreMax(self.matches)
if(self.playerTurn == 2):
res = self.exploreMin(self.matches)
if(res == -1):
self.firstPlayerWinning = False
else:
self.firstPlayerWinning = True
return res
def exploreMax(self, n):
'''
`exploreMax` function tries to find if a player has possibilities to win the game
Params :
self -- the current instance of the game
n -- a number of matches
Return :
-1 = lose or 0 = draw or +1 = win -- depends on the possibility to win of the player
'''
self.exploreMaxCalls += 1
bestVal = -1
if(self.algorithmResFound):
return 1
if(n<=0):
self.algorithmResFound = True
return 1
for i in range (1,4):
if(self.algorithmResFound):
break
res = self.exploreMin(n-i)
if(res > bestVal):
bestVal = res
if(bestVal == 1):
self.algorithmResFound = True
break
return bestVal
def exploreMin(self, n):
'''
`exploreMin` function tries to find if a player has possibilities to win the game
Params :
self -- the current instance of the game
n -- a number of matches
Return :
-1 = lose or 0 = draw or +1 = win -- depends on the possibility to win of the player
'''
self.exploreMinCalls += 1
worstVal = 1
if(self.algorithmResFound):
return -1
if(n<=0):
self.algorithmResFound = True
return -1
for i in range (1,4):
if(self.algorithmResFound):
break
res = self.exploreMax(n-i)
if(res < worstVal):
worstVal = res
if(worstVal == -1):
self.algorithmResFound = True
break
return worstVal
def __str__(self):
'''
`__str__` function overrides the default function to get a custom display when printing the game object
Params :
self -- the current instance of the game
Return :
string -- contains all the game and algorithm values
'''
content = ( "-----------------------\n"
"Game and algorithm data\n"
"-----------------------\n"
"== Game data ==\n"
f"Remaining matches : {self.matches}\n"
f"Game state : {self.state}\n"
f"Actual player : {self.playerTurn}\n"
"== Algorithm data ==\n"
f"exploreMax calls = {self.exploreMaxCalls}\n"
f"exploreMin calls = {self.exploreMinCalls}\n"
f"First player winning ? = {self.firstPlayerWinning}\n"
)
return content
game = Game(5) # Creating Nim game with 5 matches
game.miniMax() # Checking if the player 1 is winning
print(game) # Displays game and algorithm data