• AdaGrad

  • Referenced in 157 articles [sw22202]
  • advances in stochastic optimization and online learning which employ proximal functions to control the gradient...
  • Duali

  • Referenced in 26 articles [sw01245]
  • designed to solve deterministic and stochastic optimal control models of economic systems. The Duali part ... useful for teaching about dynamic deterministic and stochastic economic models. It is also a useful...
  • OPTCON

  • Referenced in 14 articles [sw02660]
  • OPTCON: An algorithm for the optimal control of nonlinear stochastic models. The authors describe ... algorithm for the optimal control of nonlinear dynamic control that allows for additive uncertainty ... well as for the presence of a stochastic parameter vector in the system equations ... Bellman’s principle of optimality to solve the problem. These two steps are repeated until...
  • SOCSol4L

  • Referenced in 2 articles [sw15008]
  • solution to a continuous-time stochastic optimal control problem. Computing the solution to a stochastic ... optimal control problem is difficult. A method of approximating ... solution to a given continuous-time stochastic optimal control problem using Markov chains was developed...
  • R-MAX

  • Referenced in 32 articles [sw02539]
  • algorithm, covering zero-sum stochastic games. (2) It has a built-in mechanism for resolving ... exploitation dilemma. (3) It formally justifies the “optimism under uncertainty” bias used in many ... algorithm for learning in single controller stochastic games. (5) It generalizes the algorithm by Monderer...
  • InfSOCSol

  • Referenced in 1 article [sw08392]
  • continuous-time in nite horizon stochastic optimal control problem. This paper describes a suite ... optimal solution to an infinite-horizon stochastic optimal control problem. The suite is an updated...
  • StOpt

  • Referenced in 10 articles [sw32903]
  • objects provided permitting to easily solve an optimization problem by regression. Different methods are available ... regressors), for underlying states following some uncontrolled Stochastic Differential Equations (python binding provided). Semi-Lagrangian ... controlled Stochastic Differential Equations (C++ only). Stochastic Dual Dynamic Programming methods to deal with stochastic ... some problems where the underlying stochastic state is controlled. Some pure Monte Carlo Methods...
  • SCAFFOLD

  • Referenced in 4 articles [sw34100]
  • SCAFFOLD: Stochastic Controlled Averaging for Federated Learning. Federated Averaging (FedAvg) has emerged as the algorithm ... propose a new algorithm (SCAFFOLD) which uses control variates (variance reduction) to correct ... usefulness of local-steps in distributed optimization...
  • DISPRO

  • Referenced in 7 articles [sw14791]
  • optimal control; ORBITAL’, unconstrained optimization and approximation [61]; NDO, nondifferentiable and stochastic optimization...
  • S-TaLiRo

  • Referenced in 20 articles [sw09775]
  • based on stochastic optimization techniques including Monte-Carlo methods and Ant-Colony Optimization. Among ... industry for model-based development of control software. We present the architecture of S-TaLiRo...
  • DualPC

  • Referenced in 10 articles [sw08479]
  • Duali/Dualpc software for quadratic-linear optimal control models. Duali (which is pronounced “dual I”) provides ... interface for deterministic, passive and active learning stochastic models as well as solvers for deterministic...
  • SReachTools

  • Referenced in 6 articles [sw30627]
  • likelihood that the state of a stochastic system will remain within a collection of time ... bounded control authority. SReachTools implements several new algorithms based on convex optimization, computational geometry ... compute over- and under-approximations of the stochastic reach set. SReachTools can be used ... closed-loop systems and can also perform controller synthesis via open-loop, affine, and state...
  • Memorize

  • Referenced in 1 article [sw30155]
  • with provable guarantees as an optimal control problem for stochastic differential equations with jumps ... cost on the reviewing frequency, the optimal reviewing schedule is given by the recall probability...
  • PGSL

  • Referenced in 11 articles [sw04748]
  • direct stochastic algorithm for global search This paper presents a new algorithm called probabilistic global ... PGSL is founded on the assumption that optimal solutions can be identified through focusing search ... tasks in areas of design, diagnosis and control...
  • OREX-J

  • Referenced in 1 article [sw07410]
  • simulation-based optimization approach for a stochastic multi-location inventory control model, and an optimization...
  • SAM

  • Referenced in 2 articles [sw04882]
  • order to be able to deal with stochastic numbers. As a consequence ... dynamically control the numerical methods used and more particularly to determine the optimal number...
  • GOP

  • Referenced in 6 articles [sw17432]
  • initialization of a given deterministic or stochastic optimization algorithm. Our objective is to improve ... performance of the considered algorithm, called core optimization algorithm, by reducing its number of cost ... approach, the core optimization is considered as a sub-optimization problem for a multi-layer ... core optimization algorithms: Steepest Descent, Heavy-Ball, Genetic Algorithm, Differential Evolution and Controlled Random Search...
  • POGTGolog

  • Referenced in 3 articles [sw32303]
  • theoretic multi-agent planning in partially observable stochastic games. In this framework, we assume ... rewards. POGTGolog allows for specifying a partial control program in a high-level logical language ... then completed by an interpreter in an optimal way. To this end, we define...
  • simontwostage

  • Referenced in 1 article [sw37355]
  • determine the minimax and optimal designs proposed by Simon (1989, Controlled Clinical Trials ... Medicine 23: 561–569). Furthermore, nonstochastic and stochastic curtailment rules can be implemented in both...