StanislavKo28/DSP_Bidder_3_rules

Intro

It's RL (Reinforcement Learning) DQN (Deep Q-Learning) model for DOOH DSP Bidder problem. The model should respect 3 rules:

• even pacing over time
• desired publishers distribution (which can be different from publishers distribution in raw bid requests flow).
• desired venue types distribution (which can be different from venue types distribution in raw bid requests flow).

Requirements.txt

torch==2.10.0
matplotlib==3.10.8
ipython==8.0.0
torchrl==0.11.1
tensordict==0.11.0
numpy==2.4.2
pandas==2.3.3

Training process

Data flow

Python all-in-one files

• dsp_bidder_3_training.py - training
• dsp_bidder_3_inference.py - testing