chore: fictious_play.py added to game theory

Author: isatyamks

game_theory/fictitious_play.py

@@ -0,0 +1,32 @@
+def fictitious_play(payoff_matrix_A, payoff_matrix_B, iterations=100):
+    n = payoff_matrix_A.shape[0]
+    m = payoff_matrix_A.shape[1]
+
+    # Initialize counts and strategies
+    counts_A = np.zeros(n)
+    counts_B = np.zeros(m)
+    strategy_A = np.ones(n) / n
+    strategy_B = np.ones(m) / m
+
+    for _ in range(iterations):
+        # Update counts
+        counts_A += strategy_A
+        counts_B += strategy_B
+
+        # Calculate best responses
+        best_response_A = np.argmax(payoff_matrix_A @ strategy_B)
+        best_response_B = np.argmax(payoff_matrix_B.T @ strategy_A)
+
+        # Update strategies
+        strategy_A = np.zeros(n)
+        strategy_A[best_response_A] = 1
+        strategy_B = np.zeros(m)
+        strategy_B[best_response_B] = 1
+
+    return strategy_A, strategy_B
+
+# Example usage
+payoff_A = np.array([[3, 0], [5, 1]])
+payoff_B = np.array([[2, 4], [0, 2]])
+strategies = fictitious_play(payoff_A, payoff_B)
+print("Fictitious Play strategies:", strategies)