FieldWalk

This game represents a search in a square graph of the shortest path. In a square of NxM, each cell has a cost that represents the cost of passing through that cell. From each cell, the player can go to one of the 4 adjacent cells (up, down, left, right). The objective is to reach the bottom-right cell [N-1,M-1] from the top-left cell [0,0] with the minimum cost.

Goal

Starting at [0,0], the goal is to reach [N-1,M-1] with the minimum cost.

Score

The score of the game is the sum of the values of the squares that the player has passed through (initial square does not count).

Import

from IArena.games.FieldWalk import FieldWalkPosition
from IArena.games.FieldWalk import FieldWalkMovement
from IArena.games.FieldWalk import FieldWalkRules

Movement

A movement is represented an int: direction.

direction - int - 0 <= direction <= 3 - Indicates the direction of the movement - Some movements are not possible if they go out of the board

Direction

Enumeration of the possible directions:

Up - 0
Down - 1
Left - 2
Right - 3

# To move up
movement = FieldWalkMovement.up()
# or
movement = FieldWalkMovement(
  direction=FieldWalkMovement.Direction.Up)

Position

A position is represented by 3 int. One indicates the x axis, other the y axis and the last one the cost to arrive to the current position.

# position : FieldWalkPosition
position.x     # X axis [0, N-1]
position.y     # Y axis [0, M-1]
position.cost  # Cost to arrive to this position

Rules

Constructor

Can receive the map, or let it be created randomly.

# Initiate with a map of 2x2 with cost 1
rules = FieldWalkRules(initial_map=FieldWalkMap([[1,1],[1,1]]))

# Initial position board 5x4 with random cost
rules = FieldWalkRules(rows=5, cols=4)

# Replicable initial position board 5x4 with random cost
rules = FieldWalkRules(rows=5, cols=4, seed=0)

Map

This game counts with a class FieldWalkMap that represents the grid of the game. This is created from a List[List[int]]. The method get_matrix() returns the list of lists with all the values.

# get the FieldWalkMap
fw_map = rules.get_map()

# Get the size
N, M = len(fw_map)
# or
N, M = fw_map.goal()

# Get the matrix of the map
fw_map.get_matrix().get_matrix()

# Get the value of the final position
value = fw_map.get_matrix()[N-1][M-1]
# or
value = fw_map[N-1,M-1]