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Utah State University is a Carnegie I Research Institute and is No. 1 in the nation in the amount of research dollars generated per faculty member. This environment allows a researcher invaluable interaction across a wide variety of active professional fields as well as an administration understanding of researcher needs.
Below are our current research projects in the field of Computer Science. These projects are headed by members of the Computer Science faculty. The faculty member in charge of the particlar research project is listed as well as a link to the project's homepage, if one exists. |
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Dr. Dan Watson |
Research Homepage |
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Space Software Laboratory |
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The Space Software Laboratory (SSL) is directed towards the development of software to support space research and defense.
Work within the laboratory focuses on programming techniques and tools for space applications. Software developed in this lab is currently flying on a number of satallite missions. We develop software for specialized processors such as the Advanced Instrument Controller (AIC) and Sentient Instrument Controller (SIC), as well as on the study of self-organizing communities of processors. |
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Dr. Vicki Allan |
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Negotiating Agents and Marital Stability |
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Funding Agency: CURI (Community/University Research Initiative Grant)
Duration: July 1,2002 through June 30, 2003 Negotiation between humans involves reacting to offers that are made (reactive) as well as making initial offers (proactive) to proposals. In the business world, software agents are able to make offers and counter-offers as well as evaluate whether a proposal should be accepted. Applications for software agents include e-commerce, auctions, manufacturing planning, scheduling, vehicle routing and financial trading This research asks the question "Can software agents be programmed to mimic human behavior so well that humans benefit from observing the automated behavior?" The idea is influenced by the class Turing Test proposed in the 1950's. In an effort to define intelligent behavior, Turing suggested a test in which a machine is asked to perform cognitive tasks via a teletype. An interrogator tries to determine whether it is a machine or a human being who is the answering the questions. In this research, we are not trying to fool anyone into thinking they are interacting with a human being when in reality a software agent is doing the negotiating. Rather, the goal is to let the agents demonstrate the role of personality attributes in negotiation. We term this tool NAMS (Negotiating Agents and Marital Stability). A couple who is considering marriage (whom we will designate as Alice and Bob) could use the tool in the following way. one agent is programmed with the personality data from Alice, while another agent is programmed with personality data from Bob. Agents will negotiate a decision for a specific scenario. Since we are trying to model the way in which partners negotiate, the specific scenario is not important. For illustrative purposes, we will assume in this document that the partners will negotiate a movie to rent. Research in the area of marital stability indicates that it is not so much how a couple differs that is important, as there will always be differences. The goals of NAMS are two fold:
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Dr. Scott Cannon |
Research Homepage |
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Space Software Laboratory |
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The Space Software Laboratory (SSL) is directed towards the development of software to support space research and defense.
Work within the laboratory focuses on programming techniques and tools for space applications. Software developed in this lab is currently flying on a number of satallite missions. We develop software for specialized processors such as the Advanced Instrument Controller (AIC) and Sentient Instrument Controller (SIC), as well as on the study of self-organizing communities of processors. |
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Dr. Donald Cooley |
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Intelligent Transportation Systems |
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In this laboratory we are working on two projects. The first is the development of a video-based intelligent transportation system. Currently, this work is aimed at building a system which, using roadside video cameras, can count and classify vehicles according to one of 13 classes. The classifier system relies heavily on the use of neural networks. The other work deals with the use of genetic algorithms for determination of optimum schedules and routes for public transit systems.
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