An anytime computation approach to information gathering (1995) [3 citations — 0 self]
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Abstract:
Information gathering systems are operating in an ever growing environment of information sources. One of the main challenges of information gathering research is to generate a high-quality response to the information needs of the user. To achieve this goal, systems will have to trade off computational resources for quality of results. This paper shows how a special type of anytime algorithms can be used efficiently to construct and monitor information gathering systems. 1 Anytime algorithms and information gathering The core of the problem of information gathering is how to generate a concise, high-quality response to the information needs of a user operating in an ever growing environment of information sources. In order to solve this problem, we can no longer rely strictly on information retrieval techniques, since the amount of "relevant " information to a given query may be too large for the user to handle. In order to reduce the amount of information and increase its precision, we need to perform some level of real-time problem solving and integration of information. The computational resources consumed by this operations will have to be balanced against the expected improvement in information quality. A similar view of information gathering has been advocated by Oates, Nagendra and Lesser [1994]. In travel planning, for example, a vacation destination is normally selected based on many factors
Citations
| 481 | An analysis of time-dependent planning – Dean, Boddy - 1988 |
| 210 | Solving TimeDependent Planning Problems – Boddy, Dean - 1989 |
| 99 | Optimal Composition of Real-Time Systems – Zilberstein, Russell - 1996 |
| 86 | Operational rationality through compilation of anytime algorithms – Zilberstein - 1993 |
| 70 | Reflection and action under scarce resources: Theoretical principles and empirical study – Horvitz, Cooper, et al. - 1989 |
| 60 | Cooperative Information Gathering: a Distributed Problem Solving Approach – Oates, Prasad, et al. - 1994 |
| 50 | Anytime sensing, planning and action: A practical model for robot control – Zilberstein, Russell - 1993 |
| 23 | Monotonically improving approximate answers to relational algebra queries – Smith, Liu - 1989 |
| 16 | Knowledge-based anytime computation – Mouaddib, Zilberstein - 1995 |
| 7 | The utility of planning – Zilberstein - 1995 |
