https://en.wikipedia.org/wiki/Monkey_and_banana_problem
"""
Definition
===============================
items = [monkey, banana, box]
positions = [0, 1, 2]
OPERATORS
===============================
Move(subject, x1, x2)
PC: monkeyAt(x1), monkeyLevelDown
A: monkeyAt(x2)
D: monkeyAt(x1)
PushBox(x1,x2)
PC: monkeyAt(x1), boxAt(x1), monkeyLevelDown
A: monkeyAt(x2), boxAt(x2)
D: monkeyAt(x1), boxAt(x1)
ClimbBox(x, direction={Up, Down})
PC: monkeyAt(x), boxAt(x), monkeyLevelDown
A: monkeyLevelUp
E: monkeyLevelDown
HaveBanana(x)
PC: monkeyAt(x), bananaAt(x), boxAt(x), monkeyLevelUp
A: GetBananaAt(x)
INITIAL STATE - Properties
===========================
monkeyAt0, monkeyLevelDown, bananaAt1, boxAt2
GOAL STATE - Properties
===========================
GetBanana(at 1)
"""
The following code will execute the default example:
python3 strips.py
Having the following (possible) output:
Initial state:
---------
{'monkeyAt0', 'bananaAt1', 'monkeyLevelDown', 'boxAt2'}
Goal state:
---------
{'haveBanana'}
STRIPS START
==============
Apply Movemonkey(0,2) to state
Apply PushBox(2,1) to state
Apply ClimbBoxUp(at 1) to state
Apply GetBanana(at 1) to state
Done! Final plan:
[Movemonkey(0,2), PushBox(2,1), ClimbBoxUp(at 1), GetBanana(at 1)]
This is an iterative version of STRIPS with heuristic based on the usage of a stack in which either Properties or Operations are pushed defining this way the sub-goals needed to reach, in a regressive approach of the search.
User is able to change the configuration of the states directly on the src/strips.py file:
initial = State()
#Simple state
initial.setProperties({"monkeyAt0", "bananaAt1", "boxAt1", "monkeyLevelDown"})
#Lab state
initial.setProperties({"monkeyAt0", "bananaAt1", "boxAt2", "monkeyLevelDown"})
goal = State()
goal.setProperties({'haveBanana'})
Code is commented for a better comprenhension.