Abstract | ||
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Smart factories are on the verge of becoming the new industrial paradigm, wherein optimization permeates all aspects of production, from concept generation to sales. To fully pursue this paradigm, flexibility in the production means as well as in their timely organization is of paramount importance. AI planning can play a major role in this transition, but the scenarios encountered in practice might be challenging for current tools. We explore the use of SMT at the core of planning techniques to deal with real-world scenarios in the emerging smart factory paradigm. We present special-purpose and general-purpose algorithms, based on current automated reasoning technology and designed to tackle complex application domains. We evaluate their effectiveness and respective merits on a logistic scenario, also extending the comparison to other state-of-the-art task planners. |
Year | DOI | Venue |
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2019 | 10.1007/978-3-030-22999-3_58 | ADVANCES AND TRENDS IN ARTIFICIAL INTELLIGENCE: FROM THEORY TO PRACTICE |
Keywords | Field | DocType |
Temporal planning,SMT,Smart factories | Automated reasoning,Software engineering,Computer science,Smart factory,Robot,Automated planning and scheduling,Satisfiability modulo theories | Conference |
Volume | ISSN | Citations |
11606 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Arthur Bit-Monnot | 1 | 0 | 0.68 |
Francesco Leofante | 2 | 16 | 5.71 |
Luca Pulina | 3 | 326 | 37.95 |
Armando Tacchella | 4 | 1448 | 108.82 |