metadata
license: unknown
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