SIP/core/a_star.py

from typing import List

from core.mushroom import Mushroom
from core.node import Node
from core.tree import Tree


def a_star(board, fringe, explored, istate, successor, get_cost, goaltest):
    agent_x = istate[0]
    agent_y = istate[1]
    agent_angle = istate[2]
    fringe: List[Node] = [Node(agent_x, agent_y, agent_angle)]

    while fringe:

        if not fringe:
            return False, False

        node = min(fringe, key=lambda x: x.cost)
        fringe.remove(node)

        if (node.x, node.y) == goaltest:
            actions = []
            while node.parent is not None:
                actions.append(node.action)
                node = node.parent
            actions.reverse()
            return actions

        explored.append(node)

        for action, x, y, angle in successor(board, node.x, node.y, node.angle):
            next_node = Node(x, y, angle)
            next_node.parent = node
            next_node.action = action
            next_node.cost = get_cost(next_node, goaltest, board) + heuristic_function(next_node, goaltest, board)

            if next_node not in fringe and next_node not in explored:
                fringe.append(next_node)
            else:
                for checked_node in fringe:
                    if checked_node == next_node and next_node.cost < checked_node.cost:
                        fringe[fringe.index(checked_node)] = next_node


def successor(board, x, y, angle):
    result = []

    result.append(("rotate_left", x, y, (angle + 1) % 4))
    result.append(("rotate_right", x, y, (angle - 1) % 4))

    if angle == 1:
        if x > 0:
            result.append(("move", x - 1, y, angle))
    elif angle == 0:
        if y > 0:
            result.append(("move", x, y - 1, angle))
    elif angle == 3:
        if x < board.col - 1:
            result.append(("move", x + 1, y, angle))
    elif angle == 2:
        if y < board.row - 1:
            result.append(("move", x, y + 1, angle))

    return result


def get_cost(node, goal: Mushroom, board):
    if (node.parent.x, node.parent.y) == (node.x, node.y):
        weight = 1
    elif isinstance((board.board[node.x][node.y]), Tree):
        weight = 1000
    elif isinstance((board.board[node.x][node.y]), Mushroom) and board.dt.predict(board.board[node.x][node.y]):
        weight = 1000
        #board.nn.predict()
    else:
        weight = 2

    return weight + node.parent.cost


def heuristic_function(node, goal, board):
    try:
        return abs(node.x - goal[0]) + abs(node.y - goal[1])
    except:
        print("No more edible mushrooms on the board. Score: " + str(board.agent.points))
        exit(0)


def bfs(istate, successor, board):
    fringe = []
    explored = []
    fringe_states = set()
    explored_states = set()

    agent_x = istate[0]
    agent_y = istate[1]
    agent_angle = istate[2]
    fringe.append(Node(agent_x, agent_y, agent_angle))
    fringe_states.add((agent_x, agent_y, agent_angle))

    while fringe:

        if not fringe:
            return False, False

        node = fringe.pop(0)
        fringe_states.remove((node.x, node.y, node.angle))

        if isinstance((board.board[node.x][node.y]), Mushroom):
            if not board.dt.predict(board.board[node.x][node.y]):
                return node.x, node.y

        explored.append(node)
        explored_states.add((node.x, node.y, node.angle))

        for action, x, y, angle in successor(board, node.x, node.y, node.angle):
            if ((x, y, angle) not in explored_states and (x, y, angle) not in fringe_states):
                next_node = Node(x, y, angle)
                next_node.parent = node
                next_node.action = action
                fringe.append(next_node)
                fringe_states.add((x, y, angle))