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Tulbatta.pdf
Iterative deepening depth-first search con Alpha-Beta Pruning
Implementata usando la libreria AIMA
MyBlackHeuristics – Euristica del nero
❖ BLACK_ALIVE: Numero di pedine nere sulla scacchiera.
❖ WHITE_EATEN: Numero di pedine bianche mangiate dal nostro giocatore.
❖ BLACK_SURROUND_KING: Numero di pedine nere che circondano il re.
❖ RHOMBUS_POSITIONS: Matrice delle posizioni favorite dei neri per bloccare le vie di
fuga.
❖ Controllo della prossima mossa del vincitore: esamina gli scacchi matti nella prossima
mossa
MyWhiteHeuristics – Euristica del bianco
❖ WHITE_ALIVE: Numero di pedine bianchesulla scacchiera.
❖ BLACK_EATEN: Numero di pedine nere mangiate dal nostro giocatore.
❖ KING_PROTECTION: Posizioni che garantiscono la sicurezza del re.
❖ NUM_ESCAPES_KING: Numero di vie di fuga vittoriose del re.
❖ BEST_POSITIONS: Le posizioni migliori per le pedine bianche a inizio partita.
❖ Controllo delle prossime mosse del vincitore: esamina gli scacchi matti nelle
prossime mosse.
L’approccio iniziale che abbiamo adottato è stata quello di usare
l’algoritmo di Montecarlo che si basa sull’idea del simulare delle
partite randomiche nel tentativo di trovare il maggior numero di
playouts vincenti.
Questa strategia per il poco tempo a disposizione per la simulazione
non riesce a restituire un risultato soddisfacente.
Monte Carlo Tree Search
Grazie per
l’attenzione!
Il team Tulbat

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Tulbatta.pdf

  • 2. Iterative deepening depth-first search con Alpha-Beta Pruning Implementata usando la libreria AIMA
  • 3. MyBlackHeuristics – Euristica del nero ❖ BLACK_ALIVE: Numero di pedine nere sulla scacchiera. ❖ WHITE_EATEN: Numero di pedine bianche mangiate dal nostro giocatore. ❖ BLACK_SURROUND_KING: Numero di pedine nere che circondano il re. ❖ RHOMBUS_POSITIONS: Matrice delle posizioni favorite dei neri per bloccare le vie di fuga. ❖ Controllo della prossima mossa del vincitore: esamina gli scacchi matti nella prossima mossa
  • 4. MyWhiteHeuristics – Euristica del bianco ❖ WHITE_ALIVE: Numero di pedine bianchesulla scacchiera. ❖ BLACK_EATEN: Numero di pedine nere mangiate dal nostro giocatore. ❖ KING_PROTECTION: Posizioni che garantiscono la sicurezza del re. ❖ NUM_ESCAPES_KING: Numero di vie di fuga vittoriose del re. ❖ BEST_POSITIONS: Le posizioni migliori per le pedine bianche a inizio partita. ❖ Controllo delle prossime mosse del vincitore: esamina gli scacchi matti nelle prossime mosse.
  • 5. L’approccio iniziale che abbiamo adottato è stata quello di usare l’algoritmo di Montecarlo che si basa sull’idea del simulare delle partite randomiche nel tentativo di trovare il maggior numero di playouts vincenti. Questa strategia per il poco tempo a disposizione per la simulazione non riesce a restituire un risultato soddisfacente. Monte Carlo Tree Search