Sequential Design for Ranking Response Surfaces

We propose and analyze sequential design methods for the problem of ranking several response surfaces. Namely, given $L \ge 2$ response surfaces over a continuous input space $\cal X$, the aim is to efficiently find the index of the minimal response across the entire $\cal X$. The response surfaces are not known and have to be noisily sampled one-at-a-time. This setting is motivated by stochastic control applications and requires joint experimental design both in space and response-index dimensions. To generate sequential design heuristics we investigate stepwise uncertainty reduction approaches, as well as sampling based on posterior classification complexity. We also make connections between our continuous-input formulation and the discrete framework of pure regret in multi-armed bandits. To model the response surfaces we utilize kriging surrogates. Several numerical examples using both synthetic data and an epidemics control problem are provided to illustrate our approach and the efficacy of respective adaptive designs.Comment: 26 pages, 7 figures (updated several sections and figures

Sequential Design for Optimal Stopping Problems

We propose a new approach to solve optimal stopping problems via simulation. Working within the backward dynamic programming/Snell envelope framework, we augment the methodology of Longstaff-Schwartz that focuses on approximating the stopping strategy. Namely, we introduce adaptive generation of the stochastic grids anchoring the simulated sample paths of the underlying state process. This allows for active learning of the classifiers partitioning the state space into the continuation and stopping regions. To this end, we examine sequential design schemes that adaptively place new design points close to the stopping boundaries. We then discuss dynamic regression algorithms that can implement such recursive estimation and local refinement of the classifiers. The new algorithm is illustrated with a variety of numerical experiments, showing that an order of magnitude savings in terms of design size can be achieved. We also compare with existing benchmarks in the context of pricing multi-dimensional Bermudan options.Comment: 24 page

Finite sample performance of sequential designs for model identification

Classical regression analysis is usually performed in two steps. In a first step an appropriate model is identified to describe the data generating process and in a second step statistical inference is performed in the identified model. An intuitively appealing approach to the design of experiment for these different purposes are sequential strategies, which use parts of the sample for model identification and adapt the design according to the outcome of the identification steps. In this paper we investigate the finite sample properties of two sequential design strategies, which were recently proposed in the literature. A detailed comparison of sequential designs for model discrimination in several regression models is given by means of a simulation study. Some non-sequential designs are also included in the study. --optimal design,robust design,discrimination design,sequential design,F-test

Sequential auction and auction design

Often an auction designer has the option of selling, or purchasing, those lots available in one auction or a sequence of auctions. In addition, bidder opportunities will not be static, in part due to arrival of information, but also because bidders can face deadlines for making decisions. This paper examines the optimal decision about how to divide what is available over time.sequential auctions

Quantum Cost Optimization for Reversible Sequential Circuit

Reversible sequential circuits are going to be the significant memory blocks for the forthcoming computing devices for their ultra low power consumption. Therefore design of various types of latches has been considered a major objective for the researchers quite a long time. In this paper we proposed efficient design of reversible sequential circuits that are optimized in terms of quantum cost, delay and garbage outputs. For this we proposed a new 3*3 reversible gate called SAM gate and we then design efficient sequential circuits using SAM gate along with some of the basic reversible logic gates.Comment: Quantum 4.12 (2013). arXiv admin note: substantial text overlap with arXiv:1312.735

Design of Sequential Circuit Using Quantum-Dot Cellular Automata (QCA)

Quantum dot cellular autometa presents a promissing nanoscale technology for replacement of conventional cmos based circuits.In this paper we introduce qca logic gates such has qca inverter and qca majority gate.This paper design the sequential logic gates.such as D latch,SR latch,JK latch,T flipflop,D flipflop,2 bit counter,4 bit shift register.These designs are captured and simulated using a design calld QCA designer