Abstract
In this paper, we revise the notion of Soft Constraint Automata, where automata transitions are weighted and consequently each action is associated with a preference value. We first relax the underlying algebraic structure that models preferences, with the purpose to use bipolar preferences (i.e., both positive and negative ones). Then, we equip automata with memory cells, that is, with an internal state to remember and update information from transition to transition. Finally, we revise automata operators, as join and hiding.
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- 1.
Francesco would like to thank Farhad for his precious mentoring during his visit at CWI as “Alain Bensoussan” Fellow during 2011–2012; Fabio for the many meetings and collaborations along the years; and Kasper for his incredible supervision job and the many interesting discussions.
- 2.
For a first-order constraint \(\phi \), the support \({\text {supp}}(\phi )\) is contained in the set of free variables \({\text {free}}(\phi )\). For example, \({\text {supp}}(x=x) = \emptyset \subseteq \{x\} = {\text {free}}(x=x)\).
- 3.
The operator is called projection in the soft framework, and \(\exists _x c\) is denoted \(c\Downarrow _{V-\{x\}}\).
- 4.
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Dokter, K., Gadducci, F., Santini, F. (2018). Soft Constraint Automata with Memory. In: de Boer, F., Bonsangue, M., Rutten, J. (eds) It's All About Coordination. Lecture Notes in Computer Science(), vol 10865. Springer, Cham. https://doi.org/10.1007/978-3-319-90089-6_6
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DOI: https://doi.org/10.1007/978-3-319-90089-6_6
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