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Restless bandits: activity allocation in a changing world
Abstract
We consider a population of n projects which in general continue to evolve whether in operation or not (although by different rules). It is desired to choose the projects in operation at each instant of time so as to maximise the expected rate of reward, under a constraint upon the expected number of projects in operation. The Lagrange multiplier associated with this constraint defines an index which reduces to the Gittins index when projects not being operated are static. If one is constrained to operate m projects exactly then arguments are advanced to support the conjecture that, for m and n large in constant ratio, the policy of operating the m projects of largest current index is nearly optimal. The index is evaluated for some particular projects.
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Citations
Cited by
The Psychology and Neuroscience of Curiosity
Kidd, C., & Hayden, B. Y. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.010 · Cited by 1,026
Relaxations of Weakly Coupled Stochastic Dynamic Programs
Adelman, D., & Mersereau, A. J. (2008) · Operations Research · doi:10.1287/opre.1070.0445 · Cited by 198
Chen, N., Kurniawan, C., Nakahira, Y., Chen, L., & Low, S. H. (2022) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2021.3138615 · Cited by 39
Industrial targeting, experimentation and long-run specialization
Klimenko, M. M. (2004) · Journal of Development Economics · doi:10.1016/j.jdeveco.2002.09.001 · Cited by 38
Metadata
- Authors
- Whittle, P.
- Venue
- Journal of Applied Probability
- Publisher
- Cambridge University Press (CUP)
- Published
- 1988
- Volume
- 25
- Issue
- A
- Pages
- 287-298
- ISSN
- 0021-9002 (ISSN-L)
- 1475-6072
- OpenAlex
- W2056921512
- Cited by
- 1,173
- References
- 0
- FWCI
- 3.76
- Type
- journal article
- Language
- en
- Open access
- closed
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- Whittle, P. (1988). Restless bandits: activity allocation in a changing world. Journal of Applied Probability. https://doi.org/10.1017/s0021900200040420
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
