On the probabilistic feasibility of solutions in multi-agent optimization problems under uncertainty
We investigate the probabilistic feasibility of randomized solutions to two distinct classes of uncertain multi-agent optimization programs. We first assume that only the constraints of the program are affected by uncertainty, while the cost function is arbitrary. Leveraging recent developments on a...
| Auteurs principaux: | , , |
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| Format: | Journal article |
| Langue: | English |
| Publié: |
Elsevier
2021
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