In biological systems, optimal strategy is generally defined as optimizing fitness, measured as reproductive value (RV), the expectation of producing surviving offspring from time t onward, given that an organism is in state S(t). Any action can be associated with an expectation of immediate reproductive success. Maximum RV results from the action that maximizes the sum of immediate and future surviving offspring. Adaptive biological behavior is the product of historical experience, heritability, individual variation, and differential fitness among individuals. Foraging tasks are a standard test bed for robot research because of their applicability to many problems. Optimal foraging theory offers explanations and predictions with direct applicability to engineering problems. Much theory development involves optimal solutions based on complete information about the system, but animals do not always conform to predictions of such models. Adaptive approximations to optimality in biological systems offer models for design of engineered systems.
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ASME 2008 Dynamic Systems and Control Conference
October 20–22, 2008
Ann Arbor, Michigan, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-4335-2
PROCEEDINGS PAPER
Optimal Foraging Theory: Lessons and Application to Adaptive Engineering Systems
John T. Lehman
John T. Lehman
University of Michigan, Ann Arbor, MI
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John T. Lehman
University of Michigan, Ann Arbor, MI
Paper No:
DSCC2008-2400, pp. 1457-1459; 3 pages
Published Online:
June 29, 2009
Citation
Lehman, JT. "Optimal Foraging Theory: Lessons and Application to Adaptive Engineering Systems." Proceedings of the ASME 2008 Dynamic Systems and Control Conference. ASME 2008 Dynamic Systems and Control Conference, Parts A and B. Ann Arbor, Michigan, USA. October 20–22, 2008. pp. 1457-1459. ASME. https://doi.org/10.1115/DSCC2008-2400
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