J. Grass and S. Zilberstein. A value-driven system for autonomous information gathering. Journal of Intelligent Information Systems, 14:5--27, 2000. Home/Search Document Not in Database Summary Related Articles Check |
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WebSifter: An Ontological Web-Mining Agent for EBusiness - Scime, Kerschberg (2001) (Correct)
....have travelled from the current page. It allows for the evaluation of page quality using the previous user comments, but the user must evaluate these comments by reading them. Search engine selection and query execution decisions are made by the Value driven Information Gathering (VDIG) system [GRAS00]. VDIG users construct decision model candidate solutions. VDIG selects the queries to be Anthony Scime and Larry Kerschberg made to find evidence in support of the candidates. However, the decision is limited to the candidate solutions identified in the decision model. This paper presents an ....
Grass, J. and Ziberstein, S.; "A Value-Driven System for Autonomous Information Gathering;" Journal of Intelligent Information Systems; Vol 14, No. 1, March 2000, pp. 5 -- 27.
Optimal Reward-Based Scheduling for Periodic Real-Time.. - Aydin, Melhem, Mosse.. (1999) (9 citations) (Correct)
....output is of no value if it is not executed completely. However, in many application areas such as multimedia applications [25] image and speech processing [5, 6, 9, 27] time dependent planning [4] robot control navigation systems [12, 29] medical decision making [13] information gathering [10], real time heuristic search [17] and database query processing [28] a partial or approximate but timely result is usually acceptable. The imprecise computation [7, 19, 21] and IRIS (Increased Reward with Increased Service) 14, 15, 18] models were proposed to enhance the resource utilization ....
.... typical in the literature since they adequately capture the behavior of many application areas like image and speech processing [5, 6, 9, 27] multimedia applications [25] time dependent planning [4] robot control navigation systems [29] real time heuristic search [17] information gathering [10] and database query processing [28] For completeness, in this paper, we show that the case of convex reward functions is an NP Hard problem and thus focus on linear and concave reward functions. Reward functions with 0 1 constraints, where no reward is accrued unless the entire optional part is ....
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J. Grass and S. Zilberstein. A Value-Driven System for Autonomous Information Gathering. Journal of Intelligent Information Systems, 14:5-27, March 2000.
Optimizing Information Exchange in Cooperative Multi-agent.. - Goldman, Zilberstein (2003) (23 citations) Self-citation (Zilberstein) (Correct)
....with communication problem. This paper is one of the few formal studies done to tackle this hard problem. It presents a promising direction based on greedy meta level control of communication that has also proved useful in meta level control of computation (e.g. 16] and information gathering [9], in which non myopic control is extremely di#cult. 2. THE THEORETICAL FRAMEWORK We present a formal model for decentralized control that is based on an extension of the decentralized partially observable Markov Decision Process. Within the model, cooperative agents are represented by finite ....
J. Grass and S. Zilberstein. A value-driven system for autonomous information gathering. Journal of Intelligent Information Systems, 14:5--27, 2000.
Monitoring And Control of anytime algorithms: a dynamic.. - Hansen, Zilberstein (2001) (13 citations) Self-citation (Zilberstein) (Correct)
....to complex problems under time constraints. Anytime algorithms are being used increasingly in a range of practical domains that include planning and scheduling [2,38] belief network and influence diagram evaluation [12,16, 36] database query processing [31,33] and information gathering [10]. By itself, however, an anytime algorithm does not provide a complete solution to Simon s challenge to make the best return decision, net of computational costs. To achieve this, a meta level control procedure in needed that determines how long to run the anytime algorithm, and when to stop and ....
J. Grass, S. Zilberstein, A value-driven system for autonomous information gathering, Intelligent Information Systems (2000), to appear.
Acquiring an Optimal Amount of Information for Choosing.. - Azoulay-Schwartz, Kraus (Correct)
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J. Grass and S. Zilberstein. A value-driven system for autonomous information gathering. Journal of Intelligent Information Systems, 14:5--27, 2000.
Using Performance Profile Trees to Improve Deliberation Control - Larson, Sandholm (2004) (Correct)
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Joshua Grass and Shlomo Zilberstein. A value-driven system for autonomous information gathering. Journal of Intelligent Information Systems, 14(1):5--27, 2000.
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