From 88eff2c4b78e02fc61b277e4c619996e4d722f8b Mon Sep 17 00:00:00 2001
From: s473575 <szypaw4@st.amu.edu.pl>
Date: Wed, 31 May 2023 21:03:00 +0200
Subject: [PATCH] Final A*

---
 src/__pycache__/agent.cpython-311.pyc      | Bin 0 -> 12477 bytes
 src/__pycache__/simulation.cpython-311.pyc | Bin 0 -> 18976 bytes
 src/agent.py                               | 291 +++++++++------------
 3 files changed, 125 insertions(+), 166 deletions(-)
 create mode 100644 src/__pycache__/agent.cpython-311.pyc
 create mode 100644 src/__pycache__/simulation.cpython-311.pyc

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HcmV?d00001

diff --git a/src/agent.py b/src/agent.py
index f4cf648..6f72c71 100644
--- a/src/agent.py
+++ b/src/agent.py
@@ -3,6 +3,20 @@ import pygame as pg
 import heapq
 
 
+class Node:
+    def __init__(self, state, parent, cost):
+        self.state = state
+        self.parent = parent
+        self.cost = cost
+
+    def __lt__(self, other):
+        return self.cost < other.cost
+
+class State:
+    def __init__(self, position, house_list):
+        self.position = position
+        self.house_list = house_list
+
 def vector_to_tuple(vector):
     tup = (int(vector.x), int(vector.y))
     return tup
@@ -27,43 +41,42 @@ class Agent:
         self.weights = {}
         self.orientation = 90
 
-
         # utworzenie grafu dróg
-        roads_pos = [vector_to_tuple(pos) for pos in self.simulation.state.road_pos_g + self.simulation.state.road_pos_r]
+        roads_pos = [vector_to_tuple(pos) for pos in
+                     self.simulation.state.road_pos_g + self.simulation.state.road_pos_r]
         roads_pos.sort()
         for index, pos in enumerate(roads_pos):
             if pos[0] < 0 or pos[0] >= 27 or pos[1] < 0 or pos[1] >= 14:
                 continue
             for another_pos in roads_pos[index:]:
-                if pos == another_pos or  another_pos[0] < 0 or another_pos[0] >= 27 or another_pos[1] < 0 or another_pos[1] >= 14:
+                if pos == another_pos or another_pos[0] < 0 or another_pos[0] >= 27 or another_pos[1] < 0 or \
+                        another_pos[1] >= 14:
                     continue
-                if ((abs(pos[0] - another_pos[0]) == 1 and abs(pos[1] - another_pos[1]) == 0) or (abs(pos[0] - another_pos[0]) == 0 and abs(pos[1] - another_pos[1]) == 1)):
+                if ((abs(pos[0] - another_pos[0]) == 1 and abs(pos[1] - another_pos[1]) == 0) or (
+                        abs(pos[0] - another_pos[0]) == 0 and abs(pos[1] - another_pos[1]) == 1)):
                     if pos not in self.graph.keys():
                         self.graph[pos] = set()
                     if another_pos not in self.graph.keys():
                         self.graph[another_pos] = set()
-                    if  another_pos in self.simulation.state.road_pos_r:
+                    if another_pos in self.simulation.state.road_pos_r:
                         weight = 1
                     elif another_pos in self.simulation.state.road_pos_g:
-                        weight = 3
+                        weight = 100
                     else:
                         weight = 1
                     self.graph[pos].add(another_pos)
                     self.graph[another_pos].add(pos)
-                    self.weights[(pos,another_pos)] = weight
+                    self.weights[(pos, another_pos)] = weight
                     self.weights[(another_pos, pos)] = weight
 
-                 
-                    
-
         # dołączenie domów i składowisk do grafu dróg
         entities = self.simulation.state.entities
         for entity in entities:
             entity_pos = vector_to_tuple(entity.position)
-            for neighbour_pos in [(entity_pos[0]-1, entity_pos[1]),
-                                  (entity_pos[0]+1, entity_pos[1]),
-                                  (entity_pos[0], entity_pos[1]-1),
-                                  (entity_pos[0], entity_pos[1]+1)]:
+            for neighbour_pos in [(entity_pos[0] - 1, entity_pos[1]),
+                                  (entity_pos[0] + 1, entity_pos[1]),
+                                  (entity_pos[0], entity_pos[1] - 1),
+                                  (entity_pos[0], entity_pos[1] + 1)]:
                 if neighbour_pos[0] < 0 or neighbour_pos[0] >= 27 or neighbour_pos[1] < 0 or neighbour_pos[1] >= 14:
                     continue
                 if neighbour_pos in roads_pos:
@@ -77,10 +90,9 @@ class Agent:
                 self.dumps[entity.trash_type] = vector_to_tuple(entity.position)
             if entity.entity_type == 'house':
                 self.houses[vector_to_tuple(entity.position)] = HousePOI()
-        
-        self.path = self.A_star()
+
+        self.path = self.a_star()
         pass
-       
 
     def update(self):
         entities = self.simulation.state.entities
@@ -90,183 +102,130 @@ class Agent:
                 self.fullness = entity.fullness
                 self.orientation = entity.orientation
 
-    
     def decide_move(self):
-        move_a = self.path[0]
-        move = (move_a[0] - self.current_pos[0], move_a[1] - self.current_pos[1])
+        if self.path:
+            move_a = self.path[0]
+            move = (move_a[0] - self.current_pos[0], move_a[1] - self.current_pos[1])
 
-        if self.orientation == 0:
-            if move[0] == 0:
-                if move[1] == -1:
-                    self.path.pop(0)
-                    return pg.Vector2(move)
-                else:
-                    return 180
-            elif move[1] == 0:
-                if move[0] == -1:
-                    return 270
-                else:
-                    return 90
-        elif self.orientation == 90:
-            if move[0] == 0:
-                if move[1] == -1:
-                    return 0
-                else:
-                    return 180
-            elif move[1] == 0:
-                if move[0] == -1:
-                    return 270
-                else:
-                    self.path.pop(0)
-                    return pg.Vector2(move)
-        elif self.orientation == 180:
-            if move[0] == 0:
-                if move[1] == -1:
-                    return 0
-                else:
-                    self.path.pop(0)
-                    return pg.Vector2(move)
-            elif move[1] == 0:
-                if move[0] == -1:
-                    return 270
-                else:
-                    return 90
+            if self.orientation == 0:
+                if move[0] == 0:
+                    if move[1] == -1:
+                        self.path.pop(0)
+                        return pg.Vector2(move)
+                    else:
+                        return 180
+                elif move[1] == 0:
+                    if move[0] == -1:
+                        return 270
+                    else:
+                        return 90
+            elif self.orientation == 90:
+                if move[0] == 0:
+                    if move[1] == -1:
+                        return 0
+                    else:
+                        return 180
+                elif move[1] == 0:
+                    if move[0] == -1:
+                        return 270
+                    else:
+                        self.path.pop(0)
+                        return pg.Vector2(move)
+            elif self.orientation == 180:
+                if move[0] == 0:
+                    if move[1] == -1:
+                        return 0
+                    else:
+                        self.path.pop(0)
+                        return pg.Vector2(move)
+                elif move[1] == 0:
+                    if move[0] == -1:
+                        return 270
+                    else:
+                        return 90
+            else:
+                if move[0] == 0:
+                    if move[1] == -1:
+                        return 0
+                    else:
+                        return 180
+                elif move[1] == 0:
+                    if move[0] == -1:
+                        self.path.pop(0)
+                        return pg.Vector2(move)
+                    else:
+                        return 90
         else:
-            if move[0] == 0:
-                if move[1] == -1:
-                    return 0
-                else:
-                    return 180
-            elif move[1] == 0:
-                if move[0] == -1:
-                    self.path.pop(0)
-                    return pg.Vector2(move)
-                else:
-                    return 90
-    
-    def heuristic(self, start, end):
-        return abs((end[0][0] - start[0][0])) + abs((end[0][1] - start[0][1])) // (abs(len(start[1]) - len(end[1])) + 1)
+            return pg.Vector2(0, 0)
 
-    def weight_cost(self, start_pos, end_pos):  
-        return self.weights[(start_pos, end_pos)]
-
-    def get_move_cost(self, start_pos, end_pos):
-        return self.heuristic(start_pos, end_pos) + self.weight_cost(start_pos, end_pos)
-
-    def get_start_state(self):
-        # entities = self.simulation.state.entities
-        # orientation - self.orientation
-        position = self.current_pos
-        house_list = tuple(self.houses)
-        start_state = (position, house_list)
-        return start_state
-
-    def get_end_state(self):
-        position = (0,1)
-        house_list = ()
-        end_state = (position, house_list)
-        return end_state
-
-    def succesor(self, state):
+    def successors(self, state):
         successors_pos = self.graph[state[0]]
         house_list = state[1]
-        successors = ()
+        successors = []
         for pos in successors_pos:
             if pos in house_list:
                 house_list = list(house_list)
                 house_list.remove(pos)
                 house_list = tuple(house_list)
 
-                successors = list(successors)
-                successors.append((pos, tuple(house_list)))
-                successors = tuple(successors)
-            else:
-                successors = list(successors)
-                successors.append((pos, tuple(house_list)))
-                successors = tuple(successors)
+            successors.append((pos, tuple(house_list)))
 
         return successors
 
+    def cost(self, current_node, succ_state):
+        if succ_state[0] not in current_node.state[1]:
+            cost = current_node.cost + self.weights[current_node.state[0], succ_state[0]]
+        else:
+            cost = float(1)
+        return cost
 
-    '''def A_star(self):
+    def heuristic(self, succ_state, goal_state):
+        position = succ_state[0]
+        if len(succ_state[1]) != 0:
+            estimated_cost = 0
+            for house in succ_state[1]:
+                estimated_cost += abs(position[0] - house[0]) + abs(position[1] - house[1])
+        else:
+            goal_position = goal_state[0]
+            estimated_cost = abs(position[0] - goal_position[0]) + abs(position[1] - goal_position[1])
+        return estimated_cost
+
+    def a_star(self):
         fringe = []
         explored = set()
-        istate = self.get_start_state()
-        goaltest = self.get_end_state()
-        node = (istate, None)
-        actions = []
+        initial_state = (self.current_pos, tuple(self.houses))
+        goal_state = (self.current_pos, ())
+        start_node = Node(initial_state, None, 0)
 
-        heapq.heappush(fringe, (self.heuristic(istate[0], goaltest[0]), node))
+        heapq.heappush(fringe, start_node)
 
         while fringe:
-            _, el = heapq.heappop(fringe)
-            elem = el[0]
-            parent = el[1]
+            current_node = heapq.heappop(fringe)
 
-            if elem == goaltest:
-                while parent is not None:
-                    actions.append(elem[0])
-                    elem = parent
-                actions.reverse()
-                return actions
+            if current_node.state == goal_state:
+                actions = []
+                while current_node:
+                    actions.append(current_node.state[0])
+                    current_node = current_node.parent
+                c = (4, 0) in actions
+                return list(reversed(actions))
 
-            explored.add(elem)
+            explored.add(current_node.state)
 
-            succs = self.succesor(elem)
-            for succ in succs:
+            succ_states = self.successors(current_node.state)
 
-                node = (succ, elem)
-                p = self.heuristic(succ[0], goaltest[0]) + self.weight_cost(elem[0], succ[0])
+            for succ_state in succ_states:
+                if succ_state in explored:
+                    continue
 
-                if succ not in explored and not any(tup[1][0] == succ for tup in fringe):
-                    heapq.heappush(fringe, (p,node))
-                elif any(tup[1] == succ for tup in fringe):
-                    i = next(i for node in enumerate(fringe) if node[1][0] == succ)
-                    if fringe[i][0] > p:
-                        fringe[i] = (p,node)
-        return actions'''
+                g = self.cost(current_node, succ_state)
+                h = self.heuristic(succ_state, goal_state)
+                succ_cost = g + h
+                succ_node = Node(succ_state, current_node, succ_cost)
 
-    def A_star(self):
-        fringe = []
-        explored = set()
-        istate = self.get_start_state()
-        goaltest = self.get_end_state()
-        node = (istate, None)
-        actions = []
-
-        heapq.heappush(fringe, (self.heuristic(istate, goaltest), node))
-
-        while fringe:
-            _, el = heapq.heappop(fringe)
-            elem = el[0]
-            parent = el[1]
-
-            if elem == goaltest:
-                while parent is not None:
-                    actions.append(elem[0])
-                    elem = parent[0]
-                    parent = parent[1]
-                actions.reverse()
-                return actions
-
-            explored.add(elem)
-
-            succs = self.succesor(elem)
-            for succ in succs:
-                node = (succ, el)
-                heuristic = self.heuristic(succ, goaltest)
-                cost = 7*self.weight_cost(elem[0], succ[0])
-                p = heuristic + cost
-
-                if succ not in explored and not any(tup[1][0] == succ for tup in fringe):
-                    heapq.heappush(fringe, (p, node))
-                elif any(tup[1][0] == succ for tup in fringe):
-                    i = next(i for i, node in enumerate(fringe) if node[1][0] == succ)
-                    if fringe[i][0] > p:
-                        fringe[i] = (p, node)
-
-        return actions
+                heapq.heappush(fringe, succ_node)
 
+        return None
 
     def discover(self):
         if self.current_pos in self.houses.keys():