Our setting is a Partially Observable Markov Decision Process with continuous state, observation and action spaces. Decisions are based on a Particle Filter for estimating the bel...
We introduce point-based dynamic programming (DP) for decentralized partially observable Markov decision processes (DEC-POMDPs), a new discrete DP algorithm for planning strategie...
— Given a finite state system with partial observers and for each observer, a regular set of trajectories which we call a secret, we consider the question whether the observers ...
Eric Badouel, Marek A. Bednarczyk, Andrzej M. Borz...
From a rare events perspective, scheduling disciplines that work well under light (exponential) tailed workload distributions do not perform well under heavy (power) tailed worklo...
In this paper, we propose TROY, the first track router with yield-driven wire planning to optimize yield loss due to random defects. As the probability of failure (POF) computed f...