* Added section on Hill Climbing

* Added images

* Updated README.md

* Added pathfinding example

* Added images

* Added mdp_apps notebook

* Added images

* LaTeX formatting errors fixed

* Modified table for TableDrivenVacuumAgent

* Add learing agent

* Add image for learning agent

* Added Policy Iteration section

* Removed ambiguous test

* Capitalized header

* Added images

* Added section for sequential decision problems

* Added vacuum_world.ipynb

* Add psource for environment

Add features like selecting cities to be part of tsp, controlling temperature and speed of
animation.

* fix small bug in knowledge.py

If hypotheses was empty, it would fail.

* add knowledge.ipynb

* fix dollar signs

* add image

* Update nlp.py

* Update test_nlp.py

* Add files via upload

* Update nlp.ipynb

* add generate_random

* Added decisiontreelearner to notebook

* Added RandomForest

* Update learning.ipynb

* Delete multilayer_perceptron.png

* Add files via upload

* Update learning.ipynb

* Add files via upload

* Update learning.ipynb

* Delete perceptron.png

* Add new Perceptron image

* Update Perceptron Implementation

* Update search.ipynb

* Delete comparision.PNG

* Delete mutation.png

* Delete Crossover.png

* Add images

* Update search.ipynb

* Update learning.py

converted method sample(self) to propety and removed the call in the statement return self.sampler

* Update search.py

minor code formatting.

* Implmented GA

Implemented Genetic Algoritm in search.py and search.ipynb

* implemented Genetic Algorithm in search.py and made modifications according to flake8. Demonstrated the working of GA iin search.ipynb.

* implemented Genetic Algorithm in search.py and made modifications according to flake8. Demonstrated the working of GA iin search.ipynb.

* Updated GA in search.ipynb

Removed the image links and included the images used in the image
folder. Reduced the file size from 2.4 MB to 183 KB. For every 21 print
statements that we previously had, now we have 2, only printing the
fittest individual in each generation. The instructions has been made to
get the detailed output.

* Delete aima-python.iml

* Delete misc.xml

* Delete modules.xml

* Delete workspace.xml

* Update learning.py

* Update search.py

* Add files via upload

* Add Perceptron Section

* Add Perceptron Image

* Delete fig_5_2.svg

* add fig_5_2.png

* Update games.ipynb

* Added Plurality Learner Plot Image

* Update learning.ipynb

* Delete knn_plot.png

* Add files via upload

this classifier of learning module is not optimized to run on this huge MNIST data

* Intro and representation of MDPs in code

* Added Image for MDP

for more uniform initialization of Agents.

Improved GUI with commands to list objects and agents.

Fixed GUI speed control (delay slider), narrowed the
range and increased the resolution.

Added three new image files and image credits file.
Better image for dirt

    1.  Unquoted Tk graphics section and created a main window for the GUI.

        Refactored code for graphical user interface, splitting EnvFrame
	into EnvGUI (main Tk window), EnvToolbar, and EnvCanvas.

    2.  Disabled binding of Mouse-1 and Mouse-2, which don't do anything 
	useful.

    3.  Implemented the add-object pop-up menu.  Defined object_classes for
	each kind of environment.

    4.  Added images for ReflexVacuumAgent and Dirt, and a get_image
	method.  get_image caches images in a dictionary to prevent
	them from being garbage-collected and avoid repeated reading
	of the same files.

        Created image files for reflex vacuum agent and dirt.

B.  Changes to XYEnvironment:

    1.  Implemented find_at method.

    2.  Implemented move_to method including bumping.

C.  Other changes -- to support bumping, defined the Obstacle class,
    and made Wall a subclass of Obstacle.  A bump occurs when an agent
    tries to move to a cell occupied by any kind of Obstacle.