We study a multiagent learning problem where agents can either learn via repeated interactions, or can follow the advice of a mediator who suggests possible actions to take. We pr...
Prior knowledge, in the form of simple advice rules, can greatly speed up convergence in learning algorithms. Online learning methods predict the label of the current point and the...
Gautam Kunapuli, Kristin P. Bennett, Amina Shabbee...
The paradigm of advisable planning, in which a user provides guidance to influence the content of solutions produced by an underlying planning system, holds much promise for impro...
This research aims at studying the effects of exchanging information during the learning process in Multiagent Systems. The concept of advice-exchange, introduced in (Nunes and Ol...
This essay gives advice to authors of papers on machine learning, although much of it carries over to other computational disciplines. The issues covered include the material that...