Data-Driven Demand Learning and Dynamic Pricing Strategies in Competitive Markets

The main merchant is Random Forest (merchant/rand_for.py or merchant/demand_learning.py).

Setup

• Install Python 3.6 or create virtual environment (e.g. virtualenv -p python3.6 env and source env/bin/activate)
• pip install -r requirements.txt
• cd merchant
• Run tests: python -m unittest

Start merchant on platform

• Go to http://vm-mpws2016hp1-02.eaalab.hpi.uni-potsdam.de/#/deployment
• Merchant API: http://vm-dynpricing-team-8.eaalab.hpi.uni-potsdam.de:<PORT>
• Set environment variables:

export PRICEWARS_MARKETPLACE_URL="vm-mpws2016hp1-04.eaalab.hpi.uni-potsdam.de:8080/marketplace"
export PRICEWARS_PRODUCER_URL="vm-mpws2016hp1-03.eaalab.hpi.uni-potsdam.de"
export PRICEWARS_KAFKA_REVERSE_PROXY_URL="vm-mpws2016hp1-05.eaalab.hpi.uni-potsdam.de:8001"
export API_TOKEN="<API TOKEN>"

• python rand_for.py --port <PORT>
• Go to http://vm-mpws2016hp1-02.eaalab.hpi.uni-potsdam.de/index.html#/config/merchant and start merchant

Reset merchant

• Stop server (Ctrl+C)
• rm ../tmp/*
• Start server (python rand_for.py --port <PORT>)

CSV interface

• rm ../tmp/*
• python rand_for.py --train <train_offers.csv> --buy <buy_offers.csv> --merchant <merchant_id> --test <test_offers.csv> --output out.txt