DOCS ON ENG: Here

pip install easymyai

, , EXE " !.exe" ( "_internal")

EasyMyAI . __ , numpy. , ( - )

:

:

```python from MyAI import AIensemble, AI

ai = AI(architecture=[10, 50, 50, 1], addbias=True, name="FirstAI")

:

ai = AIensemble(amountais=10, architecture=[10, 50, 50, 1], addbiasneuron=True, name="First_AI")

( 3 2)

ai.makeshortways((2, 3))

ai.alpha = 1e-3 #
ai.batch_size = 10 #

Adam

ai.impulse1 = 0.9 # 0.8 0.999 ai.impulse2 = 0.999 # beta1

ai.l1 = 0.0 # L1 ai.l2 = 0.0 # L2

ai.mainactfunc = ai.kitactfunc.tanh #
ai.endactfunc = ai.kitactfunc.tanh #

ai.save_dir = "Saves AIs" #

( )

for image in dataset: data = image.tolist() answer = [image.whatnum] ai.learning(data, answer, squarederror=True)

Q- ( ai.kitupdq_table)

actions = ("left", "right", "up", "down") ai.makeallforqlearning(actions, ai.kitupdqtable.standart, gamma=0.5, epsilon=0.01, qalpha=0.1)

state, reward = game.getstateandreward() ai.qlearning(state, reward, learningmethod=2.5, squarederror=False, useAdam=True, reccemode=False)

ai.make_mutations(0.05) # 5%

ai0 ai1, ai_1

ai0.geneticcrossingwith(ai1) ```

:

:

```python from MyAI import AIensemble, AI

ai = AI()

ensemble = AI_ensemble(5) # 5
```

   ,              (    Q- (   ;   ""  "" ,     -  ))

P.s. ( "learn snake.py")

:

```python ai = AI(architecture=[3, 4, 4, 4, 3], addbiasneuron=True, name="First_AI")

ensemble = AIensemble(5, architecture=[3, 4, 4, 4, 3], addbiasneuron=True, name="FirstAI") ```

```python ai = AI() ai.createweights([3, 4, 4, 4, 3], addbias=True) ai.name = "First_AI"

,

``` :

:

```python """ """

ai.alpha = 1e-3 #

ai.disabled_neurons = 0.0 #

( )

ai.batch_size = 1 # ,

( , )

( tanh

, .. )

ai.mainactfunc = ai.kitactfunc.tanh

(, tanh)

P.s. endactfunc (.. None)

ai.endactfunc = ai.kitactfunc.tanh

Adam

ai.impulse1 = 0.9 ai.impulse2 = 0.999

, ))))

( 0 ( [-1; +1]) )

ai.l1 = 0.001 # ( 0) ai.l2 = 0.01 # ( 0) ```

:

```python

data = [0, 1, 2] #
answer = [0, 1, 0] #

ai.learning(data, answer, squared_error=True) """

  (    )

""" ```

Q-:

Q- ( ) "" "" , - , ..

(0 = , <0 = , >0 = )

```python

-

allpossibleactions = ["left", "right", "up", "down"]

gamma = 0.4 # " " ( "" Q-) epsilon = 0.05 # ( ) q_alpha = 0.1 # Q- ( )

ai.makeallforqlearning(allpossibleactions, ai.kitupdqtable.standart, gamma=gamma, epsilon=epsilon, qalpha=q_alpha)

, ()

ai_state = [0, 1] #

ai.qlearning(aistate, rewardforstate, learningmethod=1, reccemode=False, squared_error=True)

( )

predict = ai.qpredict(aistate) ```

recce_mode: " " ( )

rounding: , Q- ( () - , )

rounding=0.1: 0.333333333 -> '0.3'; rounding=10: 123,456 -> 120

( learning_method ) : - 1 : "" , , ( )
,
P.s. , .. , , ( ""). _ , 1 , "" "" _ - 2 : , "". , " " (: 2.3 , 2 3 " ", 2.345 , 3.45 )

```python ai.save() #
ai.save("FirstAI") # FirstAI

ai.load("123") # "123"
```

```python

SAVES My_AI

ai.save_dir = "SAVES" ```

```python

ai0 ai1, ai_1

ai0.geneticcrossingwith(ai1) ```

• -1 1

python ai.make_mutations(0.05) # 5%

:

python ai.print_parameters()

(? , )

```python tempdata = ai.predict(data, reverse=True) newdata = ai.predict(temp_data)

new_data == data

```

, -1 1 ( 0 1)

    -1  1 (  0  1)     

```python

normalize, tanh ( sigmoid)

ai.kitactfuncs.normalize(data, 0, 1) ```

:

• !.exe ()
• _internal
  
• AI for snake
  
• AI for snake TF , " !.exe", , tensorflow Q- ( )
• AI for Tic-Tac-toe -
• Example use Q-learning , ,
  
• Games:
• - Code_Snake
  
• - GameforQ_learning "Example use Q-learning"
• - TicTactoe -
• - Swarm_Game
  
• Learning_Snakes optuna
  
• MNIST_AI mnist
• learn snake
  
• easymyai:
• - Ai_funcs Q-
• - Ai_property ( " 0 1" " ", ...)
• - CodeMyAI
  
• - EnsembleAI CodeMy_AI, ( , )
• - README
  
• setup
  

+

fun fact 2550

_ _ ()