In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
Decentralized partially observable Markov decision processes (DEC-POMDPs) form a general framework for planning for groups of cooperating agents that inhabit a stochastic and part...
Matthijs T. J. Spaan, Geoffrey J. Gordon, Nikos A....
Distributed simulation cloning technology is designed to analyze alternative scenarios of a distributed simulation concurrently within the same execution session. The goal is to o...
Dan Chen, Stephen John Turner, Boon-Ping Gan, Went...
Concurrent programming languages should be a good fit for embedded systems because they match the intrinsic parallelism of their architectures and environments. Unfortunately, typ...
A central question in quantum information theory and computational complexity is how powerful nonlocal strategies are in cooperative games with imperfect information, such as mult...
Tsuyoshi Ito, Hirotada Kobayashi, Daniel Preda, Xi...