Machine learning for function synthesis
<p>Function synthesis is the process of automatically constructing functions that satisfy a given specification. The space of functions as well as the format of the specifications vary greatly with each area of application. In this thesis, we consider synthesis in the context of satisfiability...
Päätekijä: | Parsert, J |
---|---|
Muut tekijät: | Kröning, D |
Aineistotyyppi: | Opinnäyte |
Kieli: | English |
Julkaistu: |
2024
|
Aiheet: |
Samankaltaisia teoksia
-
Reachability and escape problems in linear dynamical systems
Tekijä: Dcosta, J
Julkaistu: (2024) -
Safe and certified reinforcement learning with logical constraints
Tekijä: Hasanbeig, MH
Julkaistu: (2020) -
Synthesis of Fault-Tolerant Reliable Broadcast Algorithms With Reinforcement Learning
Tekijä: Diogo Vaz, et al.
Julkaistu: (2023-01-01) -
Parameter synthesis for parametric probabilistic dynamical systems and prefix-independent specifications
Tekijä: Baier, C, et al.
Julkaistu: (2022) -
Reinforcement Learning in the Problem of Synthesis of Majority Schemes
Tekijä: Sergey Gurov, et al.
Julkaistu: (2021-06-01)