Zobrazeno 1 - 10
of 418
pro vyhledávání: '"Peter J. Stuckey"'
Autor:
Arun S. Konagurthu, Ramanan Subramanian, Lloyd Allison, David Abramson, Peter J. Stuckey, Maria Garcia de la Banda, Arthur M. Lesk
Publikováno v:
Frontiers in Molecular Biosciences, Vol 7 (2021)
What is the architectural “basis set” of the observed universe of protein structures? Using information-theoretic inference, we answer this question with a dictionary of 1,493 substructures—called concepts—typically at a subdomain level, base
Externí odkaz:
https://doaj.org/article/9570c2ea01704adbba0e964ba24e0b65
Publikováno v:
Proceedings of the International Symposium on Combinatorial Search. 15:38-46
Multi-Train Path Finding (MTPF) is a coordination problem that asks us to plan collision-free paths for a team of moving agents, where each agent occupies a sequence of locations at any given time. MTPF is useful for planning a range of real-world ve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87d59a8b5f41b71dedc3f747ca09971d
https://doi.org/10.1609/socs.v15i1.21750
https://doi.org/10.1609/socs.v15i1.21750
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:9313-9322
Multi-Agent Path Finding (MAPF) is the problem of finding collision-free paths for multiple agents that minimize the sum of path costs. EECBS is a leading two-level algorithm that solves MAPF bounded-suboptimally, that is, within some factor w of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a6a5dc24fddb13060524785a93f5c5ac
https://doi.org/10.1609/aaai.v36i9.21162
https://doi.org/10.1609/aaai.v36i9.21162
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:3776-3785
Tree ensembles (TEs) denote a prevalent machine learning model that do not offer guarantees of interpretability, that represent a challenge from the perspective of explainable artificial intelligence. Besides model agnostic approaches, recent work pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44c2157d09a0298c97c40169f1c889f6
https://doi.org/10.1609/aaai.v36i4.20292
https://doi.org/10.1609/aaai.v36i4.20292
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:10256-10265
Multi-Agent Path Finding (MAPF) is the problem of planning collision-free paths for multiple agents in a shared environment. In this paper, we propose a novel algorithm MAPF-LNS2 based on large neighborhood search for solving MAPF efficiently. Starti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::312f1f893c1c9275e87ac31a7fe3ebb2
https://doi.org/10.1609/aaai.v36i9.21266
https://doi.org/10.1609/aaai.v36i9.21266
Autor:
Ali Ugur Guler, Emir Demirović, Jeffrey Chan, James Bailey, Christopher Leckie, Peter J. Stuckey
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:3749-3757
The predict+optimize problem combines machine learning and combinatorial optimization by predicting the problem coefficients first and then using these coefficients to solve the optimization problem. While this problem can be solved in two separate s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8d2d8d1d9ec397391106280ab7fa5a0
https://doi.org/10.1609/aaai.v36i4.20289
https://doi.org/10.1609/aaai.v36i4.20289
Autor:
Sandun Rajapaksa, Dinithi Sumanaweera, Arthur M Lesk, Lloyd Allison, Peter J Stuckey, Maria Garcia de la Banda, David Abramson, Arun S Konagurthu
Publikováno v:
Bioinformatics. 38:i255-i263
Motivation Alignments are correspondences between sequences. How reliable are alignments of amino acid sequences of proteins, and what inferences about protein relationships can be drawn? Using techniques not previously applied to these questions, by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::844bb90c57e5753e4418135eb7f1a6bc
https://doi.org/10.1093/bioinformatics/btac247
https://doi.org/10.1093/bioinformatics/btac247
Publikováno v:
Proceedings of the International Conference on Automated Planning and Scheduling. 32:169-173
Temporal Jump Point Search (JPST) is a recently introduced algorithm for grid-optimal pathfinding among dynamic temporal obstacles. In this work we consider JPST as a low-level planner in Multi-Agent Path Finding (MAPF). We investigate how the canoni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1efbcc01c60cccee133ed2e4af9dbc5
https://doi.org/10.1609/icaps.v32i1.19798
https://doi.org/10.1609/icaps.v32i1.19798
Publikováno v:
Proceedings of the International Conference on Automated Planning and Scheduling. 32:338-347
Computing time-optimal shortest paths, in road networks, is one of the most popular applications of Artificial Intelligence. This problem is tricky to solve because road congestion affects travel times. The state-of-the-art in this area is an algorit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::067f3d88af08b358aae1673a732b0b13
https://doi.org/10.1609/icaps.v32i1.19818
https://doi.org/10.1609/icaps.v32i1.19818
Autor:
Floyd Everest, Michelle Blom, Philip B. Stark, Peter J. Stuckey, Vanessa Teague, Damjan Vukcevic
Publikováno v:
Computer Security. ESORICS 2022 International Workshops ISBN: 9783031254598
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89d093d0db5497d61b4ba50b0e8c3185
https://doi.org/10.1007/978-3-031-25460-4_30
https://doi.org/10.1007/978-3-031-25460-4_30
