Lab: Informed Search and Heuristics
CSC261 - Artificial Intelligence - Weinman
- Summary:
- We explore a heuristic for the eight-puzzle problem
in preparation for implementing A* and a new heuristic.
Preparation
- Open your Scheme environment and create a new Scheme file in
your definitions pane in the same directory as your prior search files.
- Add the preparations from the prior
lab to your file:
-
;; Load definitions
(load "problem.scm")
(load "node.scm")
(load "8puzzle.scm")
;; Define the problem
(define eight-puzzle (eight-puzzle-problem))
Exercises
A: Eight puzzle heuristic
- Let's create a more difficult problem with at most ten moves from
the goal
-
(define eight-puzzle-state (random-eight-puzzle-state 10))
and display it.
-
> (display (eight-puzzle-state-board-list eight-puzzle-state))
- The function eight-puzzle-misplaced in the file 8puzzle.scm
provides the simple heuristic h1 of AIMA 3.6 (p. 103), which
is the number of misplaced (out of position) tiles. Apply this heuristic
to your state.
-
> (eight-puzzle-misplaced eight-puzzle-state)
-
Create a search node for this
state. Recall that node-init requires a heuristic procedure,
which we can now take to be eight-puzzle-misplaced.
-
(define eight-puzzle-start-node
(node-init eight-puzzle-state
eight-puzzle-misplaced))
- Query the path cost and (estimated) total cost of this start node.
-
> (node-path-cost eight-puzzle-start-node)
> (node-total-cost eight-puzzle-start-node)
Make sure these two numbers make sense to you before moving on.
- Using this heuristic function, generate the successors to your state.
-
(define successors
(problem-expand-node eight-puzzle
eight-puzzle-start-node
eight-puzzle-misplaced))
Which successor would depth-first search expand next? Make sure your
partner(s) agree about why.
- Inspect the (estimated) total cost of all the successors
-
> (map node-total-cost successors)
- Which successor would uniform-cost-search expand next?
- Which successor would A* search expand next?
For both, make sure you and your partner(s) agree about why.
B: Jumping representation
- Make sure the jump procedures are available, define a length 10 version
of the problem, and a do-nothing heuristic.
-
(load "jump.scm")
(define jump (jump-problem 10))
(define zero-fun (lambda (x) 0))
- Read the "Details" section of the header in jump.scm
to understand the Scheme-based state representation.
- Define the following (arbitrary) state for the jumping problem, making
sure you understand what it represents.
-
(define jump-state (list 10 3 2))
- Create a node for your jump state and generate its successors, just
as you did for the eight-puzzle above (A.3),
but using the uninformed heuristic zero-fun.
-
(define jump-start-node _________)
(define successors _________)
- Inspect the actions corresponding to each successor.
-
> (map node-action successors)
What do you suppose these actions mean? Confirm your intuition with
the instructor.
Lab Assignment
Between this lab and snippets in the assignment document, you now
have all the pieces necessary to implement an informed tree search!
Proceed to begin the lab's assignment.
Copyright © 2011, 2013, 2015, 2018 Jerod
Weinman.
This work is licensed under a Creative
Commons Attribution-Noncommercial-Share Alike 4.0 International License.