update projects

projects/codes/envs/windy_gridworld.py

@@ -0,0 +1,82 @@
+import gym
+import numpy as np
+import sys
+from gym.envs.toy_text import discrete
+
+UP = 0
+RIGHT = 1
+DOWN = 2
+LEFT = 3
+
+class WindyGridworldEnv(discrete.DiscreteEnv):
+
+    metadata = {'render.modes': ['human', 'ansi']}
+
+    def _limit_coordinates(self, coord):
+        coord[0] = min(coord[0], self.shape[0] - 1)
+        coord[0] = max(coord[0], 0)
+        coord[1] = min(coord[1], self.shape[1] - 1)
+        coord[1] = max(coord[1], 0)
+        return coord
+
+    def _calculate_transition_prob(self, current, delta, winds):
+        new_position = np.array(current) + np.array(delta) + np.array([-1, 0]) * winds[tuple(current)]
+        new_position = self._limit_coordinates(new_position).astype(int)
+        new_state = np.ravel_multi_index(tuple(new_position), self.shape)
+        is_done = tuple(new_position) == (3, 7)
+        return [(1.0, new_state, -1.0, is_done)]
+
+    def __init__(self):
+        self.shape = (7, 10)
+
+        nS = np.prod(self.shape)
+        n_actions = 4
+
+        # Wind strength
+        winds = np.zeros(self.shape)
+        winds[:,[3,4,5,8]] = 1
+        winds[:,[6,7]] = 2
+
+        # Calculate transition probabilities
+        P = {}
+        for s in range(nS):
+            position = np.unravel_index(s, self.shape)
+            P[s] = { a : [] for a in range(n_actions) }
+            P[s][UP] = self._calculate_transition_prob(position, [-1, 0], winds)
+            P[s][RIGHT] = self._calculate_transition_prob(position, [0, 1], winds)
+            P[s][DOWN] = self._calculate_transition_prob(position, [1, 0], winds)
+            P[s][LEFT] = self._calculate_transition_prob(position, [0, -1], winds)
+
+        # We always start in state (3, 0)
+        isd = np.zeros(nS)
+        isd[np.ravel_multi_index((3,0), self.shape)] = 1.0
+
+        super(WindyGridworldEnv, self).__init__(nS, n_actions, P, isd)
+
+    def render(self, mode='human', close=False):
+        self._render(mode, close)
+
+    def _render(self, mode='human', close=False):
+        if close:
+            return
+
+        outfile = StringIO() if mode == 'ansi' else sys.stdout
+
+        for s in range(self.nS):
+            position = np.unravel_index(s, self.shape)
+            # print(self.s)
+            if self.s == s:
+                output = " x "
+            elif position == (3,7):
+                output = " T "
+            else:
+                output = " o "
+
+            if position[1] == 0:
+                output = output.lstrip()
+            if position[1] == self.shape[1] - 1:
+                output = output.rstrip()
+                output += "\n"
+
+            outfile.write(output)
+        outfile.write("\n")