* add perceotion and tests

* upadte requirements

* fix typo

* add utils and images for perception

* fix build error

* comment the last 2 agent tests

* fix build error

* change cnn test

The "search-4e.ipynb" in line 21 is a typo for search4e.ipynb. File search-4e.ipynb does not exist. It will show 404 error.

* Implementing Class Tfidf

* added class of Tfidf
* added scoring function BM25

* Revert "Implementing Class Tfidf"

Added:
 - .coveragerc file to configure report generation
Modified:
 - .travis.yml to start generating reports during build

* add monte carlo tree search

* add comments to mcts

* change model based reflex agent

* add games4e.py

* recover games4e.ipynb

* add tests to mcts

* added text classification in nlp_apps

* updated as per the changes suggested.

Cover or use at least once in tests classes, methods, and non-debugging functions of csp.py (version 18.04.2019).  Issue #287.

* added necessary and unique tests

* some required changes

* required changes

Improvement in train_test_split function

Shuffling has been removed

Update CONTRIBUTING.md

* Update GSOC link to correctly refer aimacode@GSOC2019

* Correct the underlying typo

* Added WumpusWorld testcases

Added:
 - Testcases in test_agents.py
Modified:
 - Duplicate walls are not added in corners now

* Tests for VacuumEnvironment and WumpusEnvironment

Added:
 - Test cases for Explorer actions in WumpusEnvironment
 - Test cases for VacuumEnvironment
Modified:
 - VacuumAgent correctly disables bump percept when agent sucks dirt after bumping into a wall

* Added spaces in tuples to comply with PEP8

* Reworked Introduction and 1-D environment in agents.py

Added:
 - Table of Contents and overview
 - A miniscule explanation of all required code from agents.py
Modified:
 - Some grammar and sentences
 - Structure of the notebook in 1-D environments to make it more coherent
Removed:
 - Outputs from notebook (Makes VCS tough and bugs tough to detect)

* Reworked agents in a 2D environment

Modified:
 - Removed global variable turn from 2D park model: Agent programs are not supposed to see anything except percepts
 - Bump percept is now generated when Dog is about to bump into a wall
 - Replaced all XYEnvironment with GraphicEnvironment - Gives better readability to both code and output (Previous way of just showing GraphicEnvironment in the end was redundant imo)
 - Restructured the 2D park and EnergeticBlindDog environment scenario to be more readable
Removed:
 - Redundant Park2D without graphics (subclass of XYEnvironment)

* Fixed issue #1030

Added:
 - ipython and ipythonblocks packages to requirements.txt

* Has some typographic improvements in agents.ipynb

* Added output to agents.ipynb

* 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

* Reworked PriorityQueue spec

Modified:
- Priority Queue methods:
    queue[elem] now returns the first value of elem stored in queue
    elem in queue now correctly returns whether a copy of element is present regardless of the function value. Apparently the bug was introduced while trying to meet heapq spec
    del queue[elem] deletes the first instance of elem in queue correctly
- Algorithms
    Same change in best_first_graph_search in romania_problem.py and search.py to make them compatible with the new spec
- Tests
    Introduced 3 tests in test_utils.py to comprehensively test PriorityQueue's new spec

* Reworked PriorityQueue spec

Modified:
- Priority Queue methods:
    queue[elem] now returns the first value of elem stored in queue
    elem in queue now correctly returns whether a copy of element is present regardless of the function value. Apparently the bug was introduced while trying to meet heapq spec
    del queue[elem] delet...

* update in Readme.md

* updated as per the suggestions in the review.

* 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

* update in multimap functi n in utils.py and added test for it

* made changes according to PEP style

* broke the long sentence to 2 shorter sentences

* updated the sequence function and added test cases

* updated according to the PEP style

* improved the count function in utils.py

* updated according to PEP style

* added some test cases to first function in utils.py

* added space after each comma