* changed queue to set in AC3

Changed queue to set in AC3 (as in the pseudocode of the original algorithm) to reduce the number of consistency-check due to the redundancy of the same arcs in queue. For example, on the harder1 configuration of the Sudoku CSP the number consistency-check has been reduced from 40464 to 12562!

* re-added test commented by mistake

* added the mentioned AC4 algorithm for constraint propagation

AC3 algorithm has non-optimal worst case time-complexity O(cd^3 ), while AC4 algorithm runs in O(cd^2) worst case time

* added doctest in Sudoku for AC4 and and the possibility of choosing the constant propagation algorithm in mac inference

* removed useless doctest for AC4 in Sudoku because AC4's tests are already present in test_csp.py

* added map coloring SAT problems

* fixed typo errors and removed unnecessary brackets

* reformulated the map coloring problem

* Revert "reformulated the map coloring problem"

This reverts commit 20ab0e5afa238a0556e68f173b07ad32d0779d3b.

* Revert "fixed typo errors and removed unnecessary brackets"

This reverts commit f743146c43b28e0525b0f0b332faebc78c15946f.

* Revert "added map coloring SAT problems"

This reverts commit 9e0fa550e85081cf5b92fb6a3418384ab5a9fdfd.

* Revert "removed useless doctest for AC4 in Sudoku because AC4's tests are already present in test_csp.py"

This reverts commit b3cd24c511a82275f5b43c9f176396e6ba05f67e.

* Revert "added doctest in Sudoku for AC4 and and the possibility of choosing the constant propagation algorithm in mac inference"

This reverts commit 6986247481a05f1e558b93b2bf3cdae395f9c4ee.

* Revert "added the mentioned AC4 algorithm for constraint propagation"

This reverts commit 03551fbf2aa3980b915d4b6fefcbc70f24547b03.

* added map coloring SAT problem

* fixed build error

* Revert "added map coloring SAT problem"

This reverts commit 93af259e4811ddd775429f8a334111b9dd9e268c.

* Revert "fixed build error"

This reverts commit 6641c2c861728f3d43d3931ef201c6f7093cbc96.

* added map coloring SAT problem

* removed redundant parentheses

* added Viterbi algorithm

* added monkey & bananas planning problem

* simplified condition in search.py

* added tests for monkey & bananas planning problem

* removed monkey & bananas planning problem

* Revert "removed monkey & bananas planning problem"

This reverts commit 9d37ae0def15b9e058862cb465da13d2eb926968.

* Revert "added tests for monkey & bananas planning problem"

This reverts commit 24041e9a1a0ab936f7a2608e3662c8efec559382.

* Revert "simplified condition in search.py"

This reverts commit 6d229ce9bde5033802aca29ad3047f37ee6d870d.

* Revert "added monkey & bananas planning problem"

This reverts commit c74933a8905de7bb569bcaed7230930780560874.

* defined the PlanningProblem as a specialization of a search.Problem & fixed typo errors

* fixed doctest in logic.py

* fixed doctest for cascade_distribution

* added ForwardPlanner and tests

* added __lt__ implementation for Expr

* added more tests

* renamed forward planner

* Revert "renamed forward planner"

This reverts commit c4139e50e3a75a036607f4627717d70ad0919554.

* renamed forward planner class & added doc

* added backward planner and tests

* fixed mdp4e.py doctests

* removed ignore_delete_lists_heuristic flag

* fixed heuristic for forward and backward planners

* added SATPlan and tests

* fixed ignore delete lists heuristic in forward and backward planners

* fixed backward planner and added tests

* updated doc

* added nary csp definition and examples

* added CSPlan and tests

* fixed CSPlan

* added book's cryptarithmetic puzzle example

* fixed typo errors in test_csp

* fixed #1111

* added sortedcontainers to yml and doc to CSPlan

* added tests for n-ary csp

* fixed utils.extend

* updated test_probability.py

* converted static methods to functions

* added AC3b and AC4 with heuristic and tests

* added conflict-driven clause learning sat solver

* added tests for cdcl and heuristics

* fixed probability.py

* fixed import

* fixed kakuro

* added Martelli and Montanari rule-based unification algorithm

* removed duplicate standardize_variables

* renamed variables known as built-in functions

* fixed typos in learning.py

* renamed some files and fixed typos

* fixed typos

* fixed typos

* fixed tests

* removed unify_mm

* remove unnecessary brackets

* fixed tests

* moved utility functions to utils.py

Improvement in train_test_split function

Shuffling has been removed

* Update in NeuralNetLearner function

* made the changes as suggested

* no need of if else

* no need of if - else .   

As if hidden_layer_sizes is zero then it will not affect layer_sizes

* removed comment

* Update learning.py

* added relu activation

* added default parameters

* Correction in the formula for mean square error

* Added cross-entropy loss

* Test case for cross-entropy loss

* Decimal point mistake

* Added spaces around = and ==

* styling changes and bug fixes in learning.py

* Fix #833 and other pep corrections in mdp.py

* minor change mdp.py

* renamed train_and_test() to train_test_split() #55 #830

* typo fix

* Update learning.py

* Update test_learning.py

* added example for Decision Tree Learner

* fixed docstring in learning.py and description in learning.ipynb

* add failure_test method to utils

* comment fix

* Update test_learning.py

* Update test_csp.py

* add a simple naive bayes classifier

* Update test_learning.py

* spacing

* minor fix

* lists to strings

* Update README.md

* add powerset to utils

* add powerset test

* Create knowledge.py

* Create test_knowledge.py

* add header docstring to knowledge.py

* update learning docstring

* minor edits in knowledge.py

* Fixed truncated_svd

* Moved SVD algorithm to learning.py

* Minor fixes

* Typo fix

* Added decisiontreelearner to notebook

* Added RandomForest

* Update test_learning.py

* Update learning.py

* DataFile Update

* Update learning.py

* Update search.py

* Update test_learning.py

* Update test_text.py

* Add files via upload

* Update text.ipynb

* Update search-4e.ipynb

* Create CONTRIBUTING.md

is supposed to return an answer when errT converges, not errV
used to return size of when err_val converges but is supposed to return the size with minimum err_val

* Create function to initialize random weights

* Add sigmoid derivative function

* Fix flake8 warnings

* Remove unnecessary #noqa

* Fix doctest

* Update learning.ipynb

* Delete perceptron.png

* Add new Perceptron image

* Update Perceptron Implementation

* Add Gaussian Function

* Added Tests

Add tests for Continuous Naive Bayes + Means/Standard Deviation

* Update learning.py

* Commenting Fix

* Add test for gaussian

* test for every class

* Update test_learning.py

* Round float results to make sure test passes

* Update learning.py

* Update test_learning.py

* Update test_learning.py

* Add grade_learner

* Update test_learning.py

* Update test_learning.py

* Update learning.py

* set max_score to -1 (for now)

* Update learning.py

* Make find_max more pythonic

* Update learning.py

* Add Euclidean Distance

* Update learning.ipynb

* minor fix in notebook

* minor spacing in learning.py

* Added Euclidean Test

* Exclude test files from flake8 check

* Fix flake8 for main files

* Add flake8 check to build

* Bugfixing

* Test for "exclude"

* Update test_learning.py

* update_values

* Bug fixing

* Spacing

* Update test_agents.py

pep8 changes, showed flake8 errors

* Update test_agents.py

* Update test_agents.py

* Update test_agents.py

* Update test_text.py

added missing whitespace after comma

* Update utils.py

added space after comma

* Update search.py

added space after comma

* Update probability.py

added space after comma

* Update learning.py

added space after comma

* Update planning.py

added double_tennis_problem

* Update rl.py

In the pseudocode figure 21.8, the first 'if' starts with argument 's', which is the previous state, not s1(i.e, the current state).

* Update search.py

the 'uniform_cost_search' in notebook 'search-4e.ipynb' resembles more to the pseudocode in book.

* Update search.py

* Update search.py

* Update search.py

created a parameter size in the function leave_one_out(learner, dataset, size=None):