Výsledky vyhledávání - "Andrea, Micheli"

Synthesis of Search Heuristics for Temporal Planning via Reinforcement Learning

Autor: Andrea Micheli, Alessandro Valentini

Publikováno v: Proceedings of the AAAI Conference on Artificial Intelligence. 35:11895-11902

Automated temporal planning is the problem of synthesizing, starting from a model of a system, a course of actions to achieve a desired goal when temporal constraints, such as deadlines, are present in the problem. Despite considerable successes in t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b1853266a7e6acf469307ee044be3d83
https://doi.org/10.1609/aaai.v35i13.17413

Zobrazit plný text záznamu

Decidability and Complexity of Action-Based Temporal Planning over Dense Time

Autor: Andrea Micheli, Enrico Scala, Nicola Gigante, Angelo Montanari

Publikováno v: AAAI
Artificial Intelligence
Scopus-Elsevier

This paper studies the computational complexity of temporal planning, as represented by PDDL 2.1, interpreted over dense time. When time is considered discrete, the problem is known to be EXPSPACE-complete. However, the official PDDL 2.1 semantics, a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d4a2da94e102836e68730c643411ff5
https://doi.org/10.1609/aaai.v34i06.6539

Zobrazit plný text záznamu

Temporal Planning with Intermediate Conditions and Effects

Autor: Andrea Micheli, Alessandro Valentini, Alessandro Cimatti

Publikováno v: AAAI
Scopus-Elsevier

Automated temporal planning is the technology of choice when controlling systems that can execute more actions in parallel and when temporal constraints, such as deadlines, are needed in the model. One limitation of several action-based planning syst

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a49387257872075c9c30d68913b4b3f7
https://doi.org/10.1609/aaai.v34i06.6553

Zobrazit plný text záznamu

Deciding Unsolvability in Temporal Planning under Action Non-Self-Overlapping

Autor: Stefan Panjkovic, Andrea Micheli, Alessandro Cimatti

Publikováno v: Thirty-Sixth AAAI Conference on Artificial Intelligence

The field of Temporal Planning (TP) is receiving increasing interest for its many real-world applications. Most of the literature focuses on the TP problem of finding a plan, with algorithms that are not guaranteed to terminate when the problem admit

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9071e6e80a83f69872357f0a5136166

Zobrazit plný text záznamu

Robustness Envelopes for Temporal Plans

Autor: Alessandro Cimatti, Andrea Micheli, Michael Cashmore, Daniele Magazzeni, Parisa Zehtabi

Publikováno v: AAAI
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence
Scopus-Elsevier
Magazzeni, D, Cashmore, M, Cimatti, A, Micheli, A & Zehtabi, P 2019, Robustness Envelopes for Temporal Plans . in Proceedings of AAAI Conference on Artificial Intelligence (AAAI 2019) . https://doi.org/10.1609/aaai.v33i01.33017538

To achieve practical execution, planners must produce temporal plans with some degree of run-time adaptability. Such plans can be expressed as Simple Temporal Networks (STN), that constrain the timing of action activations, and implicitly represent t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1604e1fd598ec7ca8da12e70333e080b
https://doi.org/10.1609/aaai.v33i01.33017538

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání