initial commit

Environment.py

@@ -0,0 +1,81 @@
+import typing
+
+import networkx as nx
+import matplotlib.pyplot as plt
+
+'''
+    Build network with networkx library
+'''
+
+
+def build_network():
+    G = nx.path_graph(11)
+    G.remove_edges_from(G.edges())
+    G.add_edges_from([(0, 3), (0, 4),
+                      (1, 2), (1, 4), (1, 5), (1, 8), (1, 9),
+                      (2, 3), (2, 5), (2, 6),
+                      (5, 6), (5, 7),
+                      (7, 8),
+                      (8, 9), (8, 10),
+                      (9, 10)])
+    nx.draw(G, with_labels=True)
+    plt.show()
+
+    return G
+
+
+'''
+    Define Environment class
+    - G: networkx graph
+    - start: start-element for agent
+    - goal: goal-element for agent
+    - blocked: list of blocked nodes
+'''
+
+
+class Env:
+    def __init__(self, start: int, goal: int):
+        self.G = build_network()
+        self.start = start
+        self.goal = goal
+        self.blocked = []
+
+    '''
+        Reset the environment --> no blocked nodes
+    '''
+
+    def reset(self) -> None:
+        self.blocked = []
+
+    '''
+        Returns the next state and the reward based on state-action pait
+    '''
+
+    def get_state_reward(self, state: int, action: int) -> typing.Tuple[bool, int, int]:
+        if action == self.goal:
+            return True, 30, action
+        elif self.is_node_blocked(action):
+            return False, -5, state
+        else:
+            return False, -1, action
+
+    '''
+        Blocks node
+    '''
+
+    def block_node(self, node: int) -> None:
+        self.blocked.append(node)
+
+    '''
+        Unblocks node
+    '''
+
+    def release_node(self, node: int) -> None:
+        self.blocked.remove(node)
+
+    '''
+        Return True if node is blocked
+    '''
+
+    def is_node_blocked(self, node: int) -> int:
+        return node in self.blocked