Markov decision processes (MDPs) are controllable discrete event systems with stochastic transitions. Performances of an MDP are evaluated by a payoff function. The controller of ...
We present a class of inexact adaptive multilevel trust-region SQP-methods for the efficient solution of optimization problems governed by nonlinear partial differential equations...
This paper proposes a new multiagent planning approach to coordination synthesis that views distributed agents as discrete-event processes. The connection between discreteevent co...
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in control theory, machine learning, and discrete geometry. This c...
Verification and Simulation share many issues, one is that simulation models require validation and verification. In the context of simulation, verification is understood as the ta...