Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...
Making learning part of life is an essential challenge for inventing the future of our societies. Lifelong learning is a necessity rather than a possibility or a luxury to be cons...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
In September of 1998, the College of Engineering at the University of Massachusetts Dartmouth piloted an innovative, integrated, first-year curriculum. It dramatically changed 31 ...
Paul J. Fortier, Emily Fowler, Raymond N. Laoulach...