PuzzleSolver

Description

This command line tool illustrates the five most commonly-used searching algorithms for state-space search in modern artificial intelligence. Three algorithms represent uninformed search, while two represent informed searches. You can read more about state-space search (https://en.wikipedia.org/wiki/State_space_search).

There are also three different types of problems solved by the algorithms, as displayed here.

Synopsis

python puzzlesolver.py [algorithm_used] [configuration_file]

The following options for [algorithm_used] can be one of the following:

1. bfs - Breadth-first search (
2. ucs - Uniform-cost search
3. iddfs - Iterative-deepening depth first search
4. greedy - Greedy local search
5. a* - A* search

Dependencies

Python Interpreter (Version 2.7.1) *.config file (/examples)

Problem Types

There are three problem types listed in the PuzzleSolver application:

1. Sensor-tracking optimization problem
2. Data-aggregation problem
3. "Burnt" Pancake Problem

Sensor-tracking optimization problem

Data-aggregation problem

"Burnt" Pancake Problem