Fixed the order of alpha and beta defualt values (as found by Mervyn).

Author: BatuhanSA

pacai/agents/minimax.py

@@ -73,7 +73,7 @@ def get_action(self, state: pacai.core.gamestate.GameState) -> pacai.core.action
         self._stats_states_evaluated.append(0)
         self._stats_nodes_visited.append(0)
 
-        actions, score = self.minimax_step(state, self.ply_count + 1, math.inf, -math.inf)
+        actions, score = self.minimax_step(state, self.ply_count + 1, -math.inf, math.inf)
         action = self.rng.choice(actions)
 
         logging.debug("Turn: %d, Game State Score: %d, Minimax Score: %d, Chosen Action: %s, States Evaluated: %d, Nodes Visited: %d.",

pacai/student/multiagents.py

@@ -41,7 +41,7 @@ class MyMinimaxLikeAgent(pacai.agents.minimax.MinimaxLikeAgent):
     (you can ignore alpha and beta).
 
     To implement minimax with alpha-beta pruning,
-    minimax_step_max() and minimax_step_min() with alpha an beta are required.
+    minimax_step_max() and minimax_step_min() with alpha and beta are required.
 
     To implement expectimax, minimax_step_max() and minimax_step_expected_min() are required.