Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Francesco Percassi"'
Publikováno v:
Journal of Artificial Intelligence Research. 76:115-162
PDDL+ models are advanced models of hybrid systems and the resulting problems are notoriously difficult for planning engines to cope with. An additional limiting factor for the exploitation of PDDL+ approaches in real-world applications is the restri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af3199323a30ca266075058c0bb97f3c
https://doi.org/10.1613/jair.1.13904
https://doi.org/10.1613/jair.1.13904
Publikováno v:
Proceedings of the International Symposium on Combinatorial Search. 15:276-278
The aim of decentralised multi-agent (DMA) planning is to coordinate a set of agents to jointly achieve a goal while preserving their privacy. Blind search algorithms, such as width-based search, have recently proved to be very effective in the conte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::473e5ddd3de41d65651719c302e71c31
https://doi.org/10.1609/socs.v15i1.21784
https://doi.org/10.1609/socs.v15i1.21784
Autor:
Alfonso Gerevini, Nir Lipovetzky, Nico Peli, Francesco Percassi, Alessandro Saetti, Ivan Serina
Publikováno v:
Proceedings of the International Symposium on Combinatorial Search. 10:79-87
In multi-agent planning, agents jointly compute a plan that achieves mutual goals, keeping certain information private to the individual agents. Agents' coordination is achieved through the transmission of messages, but they can be a source of privac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f2a81ba12461788aeed6b49ada6b5c7
https://doi.org/10.1609/socs.v10i1.18505
https://doi.org/10.1609/socs.v10i1.18505
Publikováno v:
Proceedings of the International Conference on Automated Planning and Scheduling. 29:320-328
We address the problem of propositional planning extended with the class of soft temporally extended goals supported in PDDL3, also called qualitative preferences since IPC-5. Such preferences are useful to characterise plan quality by allowing the u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ebf2ab4090df406a5ac33f0e2c6ea9dd
https://doi.org/10.1609/icaps.v29i1.3494
https://doi.org/10.1609/icaps.v29i1.3494
Publikováno v:
AIxIA 2021 – Advances in Artificial Intelligence ISBN: 9783031084201
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5653aaad0dcc710ac01788d971749ffc
https://hdl.handle.net/11379/569605
https://hdl.handle.net/11379/569605
PDDL+ allows the formal specification of systems representing mixed discrete-continuous representation, under both discrete and continuous dynamics; this expressiveness is pivotal in real-world applications. An important aspect is the capability of v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3494f2f5f393e8650a46bc699c0ea139
https://hdl.handle.net/11379/569608
https://hdl.handle.net/11379/569608
We tackle the problem of classical planning with qualitative state-trajectory constraints as those that can be expressed in PDDL3. These kinds of constraints allow a user to formally specify which temporal properties a plan has to conform with throug
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ac659aba8d0cde7268984f5678e147e
https://hdl.handle.net/11379/569806
https://hdl.handle.net/11379/569806
Automated planning is a prominent Artificial Intelligence (AI) challenge that has been extensively studied for decades, which has led to the development of powerful domain-independent planning syst...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fbf913a422a72c9480db18e4e61480ff
http://hdl.handle.net/11379/549095
http://hdl.handle.net/11379/549095
Autor:
Alfonso Gerevini, Nir Lipovetzky, Alessandro Saetti, Francesco Percassi, Ivan Serina, Gabriele Bazzotti
Publikováno v:
AI*IA 2018 – Advances in Artificial Intelligence ISBN: 9783030038397
AI*IA
Università degli Studi di Brescia-IRIS
AI*IA
Università degli Studi di Brescia-IRIS
In multi-agent planning, preserving the agents’ privacy has become an increasingly popular research topic. In multi-agent privacy-preserving planning, agents jointly compute a plan that achieves mutual goals by keeping certain information private t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d8f7dc11c7ece3f6bd9e77f92d9303b9
https://doi.org/10.1007/978-3-030-03840-3_32
https://doi.org/10.1007/978-3-030-03840-3_32