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Scientific and Technical Aerospace Reports Volume 38 July 28, 2000

Scientific and Technical Aerospace Reports Volume 38 July 28, 2000

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ecoming almost too cumbersome to be useful. The emergence of Digital Video Disks Recorder (DVD-R) technology promises<br />

to reduce the number of discs required for archive applications by a factor of seven while providing improved reliability. It is<br />

important to identify problem areas for DVD-R media <strong>and</strong> provide guidelines to manufacturers, file system developers <strong>and</strong> users<br />

in order to provide reliable data storage <strong>and</strong> interchange. The Data Distribution Laboratory (DDL) at NASA’s Jet Propulsion Laboratory<br />

began its evaluation of DVD-R technology in early 1998. The initial plan was to obtain a DVD-Recorder for preliminary<br />

testing, deploy reader hardware to user sites for compatibility testing, evaluate the quality <strong>and</strong> longevity of DVD-R media <strong>and</strong><br />

develop proof-of-concept archive collections to test the reliability <strong>and</strong> usability of DVD-R media <strong>and</strong> jukebox hardware.<br />

Derived from text<br />

Digital Data; Digital Television; Multimedia; Video Disks; Video Communication<br />

<strong>2000</strong>0063523 Lamont-Doherty Geological Observatory, Palisades, NY USA<br />

Enhancement of the Release of <strong>Scientific</strong> Data in the Framework of <strong>Scientific</strong> Publishing Annual Report, 1 Mar. 1999 -<br />

29 Feb. <strong>2000</strong><br />

Scholosser, Peter; Apr. 20, <strong>2000</strong>; 4p; In English<br />

Contract(s)/Grant(s): N00014-99-1-0461<br />

Report No.(s): AD-A376915; LDEO-5-21802; No Copyright; Avail: CASI; A01, Hardcopy; A01, Microfiche<br />

This proposal requested support for exploring a more rapid data release in the framework of the Journal of Geophysical<br />

Research (Oceans) Editorship. The goal is to develop a policy that would require data release at the same time as publication of<br />

the first scientific description of the research project that produced the data. Design <strong>and</strong> implementation of the policy should<br />

emphasize incentives <strong>and</strong> advantages of early data release in terms of possibilities of cooperation <strong>and</strong> the opportunity for the community<br />

to develop large integrated data sets to derive synthesized science products.<br />

DTIC<br />

Research Management; Documents; Geophysics; Data Processing<br />

<strong>2000</strong>0064523 Jet Propulsion Lab., California Inst. of Tech., Pasadena, CA USA<br />

A Review of the New AVIRIS Data Processing System<br />

Aronsson, Mikael, Jet Propulsion Lab., California Inst. of Tech., USA; Summaries of the Seventh JPL Airborne Earth Science<br />

Workshop January 12-16, 1998; Dec. 19, 1998; <strong>Volume</strong> 1, pp. 15-21; In English; See also <strong>2000</strong>0064520; No Copyright; Avail:<br />

CASI; A02, Hardcopy; A04, Microfiche<br />

The processing of AVIRIS data - from the Metrum Very Large Data Store (VLDS) flight tape to delivered data products -<br />

has traditionally been performed in essentially the same way, from the beginning of the AVIRIS project up to <strong>and</strong> including the<br />

1996 flight season. Starting with the 1997 flight season, a drastically different paradigm has been used for the processing of AVI-<br />

RIS data. This change was made possible by the recent development of <strong>and</strong> related availability of affordable data storage devices.<br />

Derived from text<br />

Data Processing Equipment; Data Storage; Data Processing; Magnetic Tapes; Magnetic Disks<br />

<strong>2000</strong>0064582 NASA Ames Research Center, Moffett Field, CA USA<br />

Adaptivity in Agent-Based Routing for Data Networks<br />

Wolpert, David H., NASA Ames Research Center, USA; Kirshner, Sergey, NASA Ames Research Center, USA; Merz, Chris J.,<br />

NASA Ames Research Center, USA; Turner, Kagan, NASA Ames Research Center, USA; Welcome to the NASA High Performance<br />

Computing <strong>and</strong> Communications Computational Aerosciences (CAS) Workshop <strong>2000</strong>; February <strong>2000</strong>; In English; See<br />

also <strong>2000</strong>0064579; No Copyright; Abstract Only; Available from CASI only as part of the entire parent document<br />

This article introduces the concept of ”COllective INtelligence” (COIN) <strong>and</strong> the crucial steps involved in COIN design. A<br />

COIN is a large multi-agent system where: (i) There is no centralized communication among agents; (ii) There is no centralized<br />

control among agents; (iii) There is a well-specified global objective, <strong>and</strong> we are confronted with the inverse problem of how to<br />

configure the system to achieve that objective. (iv) Agents are ”greedy” in that they act to try to optimize their own utilities, without<br />

explicit regard to cooperation with other agents. Many conventional approaches to designing large distributed systems to optimize<br />

a world utility attempt to explicitly model the dynamics of the overall system. They then h<strong>and</strong>-tune the interactions between the<br />

agents to ensure that those agents ”cooperate” as far as the world utility is concerned. This approach is labor-intensive, often results<br />

in highly nonrobust systems, <strong>and</strong> usually results in design techniques that have limited applicability. In contrast, in our approach<br />

we wish to solve the COIN design problems implicitly, via the ”adaptive” character of Reinforcement Learning (RL) algorithms<br />

that each of the agents run. This approach introduces an entirely new, profound design problem: Assuming the RL algorithms are<br />

able to achieve high rewards, what reward functions for the individual agents will, when pursued by those agents, result in high<br />

world utility? How, without any detailed modeling of the overall system, can one set the utility functions for the RL algorithms<br />

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