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An asymptotically optimal multiversion B-tree

by Bruno Becker, Stephan Gschwind, Thomas Ohler, Bernhard Seeger, Peter Widmayer , 1996
"... In a variety of applications, we need to keep track of the development of a data set over time. For maintaining and querying these multiversion data efficiently, external storage structures are an absolute necessity. We propose a multiversion B-tree that supports insertions and deletions of data ite ..."
Abstract - Cited by 184 (9 self) - Add to MetaCart
items at the current version and range queries and exact match queries for any version, current or past. Our multiversion B-tree is asymptotically optimal in the sense that the time and space bounds are asymptotically the same as those of the (single-version) B-tree in the worst case. The technique we

Optimistic Agents are Asymptotically Optimal

by Peter Sunehag, Marcus Hutter , 2012
"... We use optimism to introduce generic asymptotically optimal reinforcement learning agents. They achieve, with an arbitrary finite or compact class of environments, asymptotically optimal behavior. Furthermore, in the finite deterministic case we provide finite error bounds. ..."
Abstract - Cited by 5 (5 self) - Add to MetaCart
We use optimism to introduce generic asymptotically optimal reinforcement learning agents. They achieve, with an arbitrary finite or compact class of environments, asymptotically optimal behavior. Furthermore, in the finite deterministic case we provide finite error bounds.

Asymptotically Optimal Agents

by Tor Lattimore, Marcus Hutter, Eth Zürich , 2011
"... Artificial general intelligence aims to create agents capable of learning to solve arbitrary interesting problems. We define two versions of asymptotic optimality and prove that no agent can satisfy the strong version while in some cases, depending on discounting, there does exist a non-computable w ..."
Abstract - Cited by 9 (7 self) - Add to MetaCart
Artificial general intelligence aims to create agents capable of learning to solve arbitrary interesting problems. We define two versions of asymptotic optimality and prove that no agent can satisfy the strong version while in some cases, depending on discounting, there does exist a non

AN ASYMPTOTIC OPTIMAL DESIGN

by Kamel Rekab
"... The problem of designing an experiment to estimate the product of the means of two normal populations is considered. A Bayesian approach is adopted in which the product of the means is estimated by its posterior mean. A fully sequential design is proposed and shown to be asymptotically optimal. ..."
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The problem of designing an experiment to estimate the product of the means of two normal populations is considered. A Bayesian approach is adopted in which the product of the means is estimated by its posterior mean. A fully sequential design is proposed and shown to be asymptotically optimal.

Asymptotically optimal covering designs

by Daniel M. Gordon, Greg Kuperberg, Oren Patashnik, Joel H. Spencer - JOURNAL OF COMBINATORIAL THEORY, SERIES A , 1995
"... A (v,k,t) covering design, or covering, is a family of k-subsets, called blocks, chosen from a v-set, such that each t-subset is contained in at least one of the blocks. The number of blocks is the covering’s size, and the minimum size of such a covering is denoted by C(v,k,t). It is easy to see tha ..."
Abstract - Cited by 11 (3 self) - Add to MetaCart
for constructing good coverings, and gave tables of upper bounds on C(v,k,t) for small v, k, and t. The present paper shows that two of those constructions are asymptotically optimal: For fixed k and t, the size of the coverings constructed matches Rödl’s bound. The paper also makes the o(1) error bound explicit

ASYMPTOTICALLY OPTIMAL MARKET MECHANISMS

by Tymon Tatur , 2001
"... Because rational agents use their private information strategically in many trading environments any budget balanced, incentive compatible, and individually rational market mechanism will be inefficient. This paper is concerned with the emerging inefficiencies as the number of traders becomes large. ..."
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is budget balanced, individually rational, implementable in dominant strategies, and asymptotically optimal in the sense that it achieves the above rate of convergence. As a side product of our analysis we get other asymptotic results describing the trade off between revenue and efficiency. For example, we

Asymptotic Optimality of Balanced Routing

by Hong Chen, Heng-qing Ye , 2010
"... Consider a system with K parallel single-servers, each with its own waiting room. Upon arrival, a job is to be routed to the queue of one of the servers. Finding routing policy that minimizes the total workload in the system is a known difficult problem in general. Even if the optimal policy is iden ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
for any fixed c ≥ 2 is asymptotically optimal in the sense that it minimizes the workload over all time in the diffusion limit. In addition, the policy helps to distribute works among all the servers evenly.

Asymptotically Optimal Geometric Mobile Ad-Hoc Routing

by Fabian Kuhn, Roger Wattenhofer, Aaron Zollinger , 2002
"... In this paper we present AFR, a new geometric mobile adhoc routing algorithm. The algorithm is completely distributed; nodes need to communicate only with direct neighbors in their transmission range. We show that if a best route has cost c, AFR finds a route and terminates with cost O(c ) in the ..."
Abstract - Cited by 130 (11 self) - Add to MetaCart
(c ) in the worst case. AFR is the first algorithm with cost bounded by a function of the optimal route. We also give a tight lower bound by showing that any geometric routing algorithm has worst-case ). Thus AFR is asymptotically optimal. We give a non-geometric algorithm that also matches the lower bound

On asymptotically optimal meshes by coordinate transformation

by Guillermo D. Cañas, Steven J. Gortler - In Proceedings of 15th International Meshing Roundtable , 2006
"... Summary. We study the problem of constructing asymptotically optimal meshes with respect to the gradient error of a given input function. We provide simpler proofs of previously known results and show constructively that a closed-form solution exists for them. We show how the transformational method ..."
Abstract - Cited by 5 (3 self) - Add to MetaCart
Summary. We study the problem of constructing asymptotically optimal meshes with respect to the gradient error of a given input function. We provide simpler proofs of previously known results and show constructively that a closed-form solution exists for them. We show how the transformational

Asymptotic optimality Large deviations

by unknown authors
"... Moment condition Generalized method of moments Generalized empirical likelihood necessarily satisfy existing conditions for optimality but does satisfy our new conditions; and (ii) the generalized method of moments (GMM) test and the generalized empirical likelihood (GEL) tests are Hodges–Lehmann op ..."
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–Lehmann optimal under mild primitive conditions. These results support the belief that the Hodges–Lehmann optimality is a weak asymptotic requirement. © 2012 Elsevier B.V. All rights reserved. 1.
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