%0 Journal Article %1 wang2020sequential %A Wang, Junqi %A Wang, Pei %A Shafto, Patrick %D 2020 %K bayesian readings %T Sequential Cooperative Bayesian Inference %U http://arxiv.org/abs/2002.05706 %X Cooperation is often implicitly assumed when learning from other agents. Cooperation implies that the agent selecting the data, and the agent learning from the data, have the same goal, that the learner infer the intended hypothesis. Recent models in human and machine learning have demonstrated the possibility of cooperation. We seek foundational theoretical results for cooperative inference by Bayesian agents through sequential data. We develop novel approaches analyzing consistency, rate of convergence and stability of Sequential Cooperative Bayesian Inference (SCBI). Our analysis of the effectiveness, sample efficiency and robustness show that cooperation is not only possible in specific instances but theoretically well-founded in general. We discuss implications for human-human and human-machine cooperation.

@article{wang2020sequential, abstract = {Cooperation is often implicitly assumed when learning from other agents. Cooperation implies that the agent selecting the data, and the agent learning from the data, have the same goal, that the learner infer the intended hypothesis. Recent models in human and machine learning have demonstrated the possibility of cooperation. We seek foundational theoretical results for cooperative inference by Bayesian agents through sequential data. We develop novel approaches analyzing consistency, rate of convergence and stability of Sequential Cooperative Bayesian Inference (SCBI). Our analysis of the effectiveness, sample efficiency and robustness show that cooperation is not only possible in specific instances but theoretically well-founded in general. We discuss implications for human-human and human-machine cooperation.}, added-at = {2020-02-17T22:26:45.000+0100}, author = {Wang, Junqi and Wang, Pei and Shafto, Patrick}, biburl = {https://www.bibsonomy.org/bibtex/23b04439997575675cbc69ea495705f1a/kirk86}, description = {[2002.05706] Sequential Cooperative Bayesian Inference}, interhash = {c9457cab453b9dbb63a51184501cc3ed}, intrahash = {3b04439997575675cbc69ea495705f1a}, keywords = {bayesian readings}, note = {cite arxiv:2002.05706Comment: 28 pages, 22 figures, submitted to ICML 2020}, timestamp = {2020-02-17T22:26:45.000+0100}, title = {Sequential Cooperative Bayesian Inference}, url = {http://arxiv.org/abs/2002.05706}, year = 2020 }