Многоагентное обучение с подкреплением

We use single-agent and multi-agent Rein- forcement Learning (RL) for learning dia- logue policies in a resource allocation ne- gotiation scenario. Two agents learn con- currently by interacting with each …...

AbstractWith counterfactual bandit learning, models can be trained based on positive and negative feedback received for historical predictions, with no labeled data needed. Such feedback is often available in real-world …...