The document discusses using deep learning decision making with robotic process automation (RPA). It proposes configuring known features and an unknown business logic as inputs for a deep learning model in the RPA environment. The model would be trained on a dataset generated by crawling sample data 1,000 times without preprocessing. The trained model could then be used by an RPA bot to make automated decisions by requesting data, getting a response from the model, and taking action accordingly. Code requirements and files for implementing this deep learning decision making RPA are also listed.

1. 로보틱스 업무 자동화(RPA)
DEEP-LEARNING DECISION MAKING with RPA
2019.08.05.

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Question for Deep-Learning Decision Making RPA
Discover Black Box Process (“Unknown Business Logic”)
Given Features
Process
RPA
Human Decision
Decision
Flow
ON BOT PC
BLACK BOX PROCESS
NOT (Something) + (Something) = 5
10 (Somethig) 2 = 5
PROCESS AUTOMATION NEEDS DEEP DECISION MAKING
RATHER THAN DEEP COGNITIVE TECH

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Realization Steps for Deep-Learning Decision Making RPA
Configure Features In RPA Environment
- Features should be found in PC
X1 = News Cast ID (“NC_{Digits}”)
X2 = Relative Page Number
<Known Features>
Y = 0 OR 1
<Final Decision>
<Unknown Business Logic>
BLACK BOX PROCESS
<ANSWER For Unknown Business Logic>
IF (Digits from X1 can be divided by X2) AND (X2 is not 1), THEN Y = 1
ELSE Y = 0

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Realization Steps for Deep-Learning Decision Making RPA
Crawling Train Dataset For DDM Model
* 1,000 Times Refresh
Extracting Train Data
No preprocess in crawling

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Realization Steps for Deep-Learning Decision Making RPA
Deep-Learning Decision Making RPA – REQ/RES PROCESS
BOT
Gain Features
Request Data DDM Model
Handing
BLACK BOX PROCESS
Making Decision
Handing
Response Data
BOT
DO
Decision
Flow
Trained

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Realization Steps for Deep-Learning Decision Making RPA
Deep-Learning Decision Making RPA – REQ/RES PROCESS
Model
Request Data Response Data
BOT Activity Per Decision

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Realization Steps for Deep-Learning Decision Making RPA
How to run Source Code
DDM_Model.py
# Requirements
1. Numpy – pip install numpy
2. Pandas – pip install pandas
3. Sklearn – pip install sklearn
4. Keras (tensorflow) – pip install tensorflow; pip install keras
“DEEP_WORK.zipDEEP_WORKDEEP_DECISION_MAKING_RPADEEP_DECISION_MAKING.xaml”
MAIN XAML FILE