Auto Topic: mayne
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definitionpros_cons
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mayne
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| Source | Type | Target | W |
|---|---|---|---|
| Auto Topic: jacobson | CO_OCCURS | Auto Topic: mayne | 3 |
Evidence Chunks
| Source | Confidence | Mentions | Snippet |
|---|---|---|---|
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... mpling algorithms for filtering (also called sequential Monte Carlo methods) were developed in the control theory community by Handschin and Mayne (1969), and the re- sampling idea that is the core of particle filtering appeared in a Russian control journal (Zarit- skii et al., 197 ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... d control and is due to Li and Todorov (2004). It is a variant of the much older differential dynamic program- ming technique (Jacobson and Mayne, 1970). |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... d control and is due to Li and Todorov (2004). It is a variant of the much older differential dynamic program- ming technique (Jacobson and Mayne, 1970). 986 Chapter 26 Robotics Fine-motion planning with limited sensing was investigated by Lozano-Perezet al. (1984) and Canny and ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... tivation, silencing, and desynchronization of neural activity, with single-spike temporal resolution. PLoS One, e299. Handschin, J. E. and Mayne, D. Q. (1969). Monte Carlo techniques to estimate the conditional expecta- tion in multi-stage nonlinear filtering. Int. J. Control, 9, ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... kkola, T. and Jordan, M. I. (1996). Computing upper and lower bounds on likelihoods in intractable networks. In UAI-96. Jacobson, D. H. and Mayne, D. Q. (1970).Differential Dynamic Programming. North-Holland. Jaderberg, M., Czarnecki, W. M., Dunning, I., Mar- ris, L., Lever, G., ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... separator, 710, 711 maximum mean discrepancy, 737 max norm, 564 Maxwell, J., 34, 426, 1027, 1105 Mayer, A., 127, 1098 Mayer, J., 734, 1105 Mayne, D. Q., 516, 985, 1098, 1100 Mayor, A., 1057, 1105 Maziarz, K., 736, 1072, 1112 MBP (planning system), 401 McAfee, A., 1062, 1089 McAl ... |