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pro vyhledávání: '"Williams, Brian Charles"'
Autor:
Williams, Brian Charles
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1989.
Includes bibliographical references (leaves 293-297).
by Brian Charles Williams.
Ph.D.
Includes bibliographical references (leaves 293-297).
by Brian Charles Williams.
Ph.D.
Externí odkaz:
http://hdl.handle.net/1721.1/39954
Akademický článek
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Publikováno v:
MIT web domain
Autonomous agents operating in partially observable stochastic environments often face the problem of optimizing expected performance while bounding the risk of violating safety constraints. Such problems can be modeled as chance-constrained POMDP’
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________88::a9f448f2ac5ec7f4c645e9e7b0f25dc8
https://orcid.org/0000-0002-1057-3940
https://orcid.org/0000-0002-1057-3940
Publikováno v:
Wang
Temporal uncertainty in large-scale logistics forces one to trade off between lost efficiency through built-in slack and costly replanning when deadlines are missed. Due to the difficulty of reasoning about such likelihoods and consequences, a comput
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________88::f2d46ec773aab41ac2624510319a2e3d
https://orcid.org/0000-0002-1057-3940
https://orcid.org/0000-0002-1057-3940
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
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Publikováno v:
MIT web domain
This paper presents a novel algorithm for finite-horizon optimal control problems subject to additive Gaussian-distributed stochastic disturbance and chance constraints that are defined over feasible, non-convex state spaces. Our previous work [1] pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________88::20e24eee33f1104ea937bff0e05cf4ec
http://hdl.handle.net/1721.1/67723
http://hdl.handle.net/1721.1/67723
Autor:
Ono, Masahiro, Williams, Brian Charles
Publikováno v:
MIT web domain
This paper proposes Market-based Iterative Risk Allocation (MIRA), a new market-based distributed planning algorithm for multi-agent systems under uncertainty. In large coordination problems, from power grid management to multi-vehicle missions, mult
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________88::29b0e8f903643ec591315fc675cc89aa
https://orcid.org/0000-0002-1057-3940
https://orcid.org/0000-0002-1057-3940
Publikováno v:
MIT web domain
In this paper we extend dynamic controllability of temporally-flexible plans to temporally-flexible reactive programs. We consider three reactive programming language constructs whose behavior depends on runtime observations; conditional execution, i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________88::2840d43fba82808e69c21555182b9dce
http://hdl.handle.net/1721.1/67835
http://hdl.handle.net/1721.1/67835
Publikováno v:
MIT web domain
Dynamic plan execution strategies allow an autonomous agent to respond to uncertainties while improving robustness and reducing the need for an overly conservative plan. Executives have improved this robustness by expanding the types of choices made
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________88::1ac173eb2127630ad7e8c131d3537dd3
https://orcid.org/0000-0002-1057-3940
https://orcid.org/0000-0002-1057-3940
Publikováno v:
MIT web domain
An essential quality of a good partner is her responsiveness to other team members. Recent work in dynamic plan execution exhibits elements of this quality through the ability to adapt to the temporal uncertainties of others agents and the environmen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________88::4d1d5b1d7d7511e74d4256bb40d2abfd
https://orcid.org/0000-0002-1057-3940
https://orcid.org/0000-0002-1057-3940