Abstract--The difficulties encountered in sequential decisionmaking problems under uncertainty are often linked to the large size of the state space. Exploiting the structure of th...
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mik...
Online popularity has enormous impact on opinions, culture, policy, and profits, especially with the advent of the social Web and Web advertising. Yet the processes that drive popu...
Jacob Ratkiewicz, Filippo Menczer, Santo Fortunato...
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Agents that operate in a real-world environment have to process an abundance of information, which may be ambiguous or noisy. We present a method inspired by cognitive research tha...
Maria E. Niessen, Gert Kootstra, Sjoerd de Jong, T...