NeurIPS 2017poster32 citations
Multi-View Decision Processes: The Helper-AI Problem
Christos Dimitrakakis, David C. Parkes, Goran Radanovic, Paul Tylkin
Abstract
We consider a two-player sequential game in which agents have the same reward function but may disagree on the transition probabilities of an underlying Markovian model of the world. By committing to play a specific policy, the agent with the correct model can steer the behavior of the other agent, and seek to improve utility. We model this setting as a multi-view decision process, which we use to formally analyze the positive effect of steering policies. Furthermore, we develop an algorithm for computing the agents' achievable joint policy, and we experimentally show that it can lead to a large utility increase when the agents' models diverge.
BibTeX
@inproceedings{NIPS2017_227f6afd,
author = {Dimitrakakis, Christos and Parkes, David C and Radanovic, Goran and Tylkin, Paul},
booktitle = {Advances in Neural Information Processing Systems},
editor = {I. Guyon and U. Von Luxburg and S. Bengio and H. Wallach and R. Fergus and S. Vishwanathan and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Multi-View Decision Processes: The Helper-AI Problem},
url = {https://proceedings.neurips.cc/paper_files/paper/2017/file/227f6afd3b7f89b96c4bb91f95d50f6d-Paper.pdf},
volume = {30},
year = {2017}
}