The phrase "actor system" is correct and usable in written English.
It can be used in the context of computer science, particularly in reference to a model of computation that uses "actors" as the fundamental units of computation.
Example: "The actor system allows for concurrent processing by enabling multiple actors to communicate with each other asynchronously."
Alternatives: "actor model" or "actor framework".
We implement a concurrent version of adaptive quadrature as an actor system.
The ACToR system is implemented using 100% open-source software, MySQL for the database development, Perl for loading data and Java for web interface development.
In addition, the ToxRefDB makes it possible to link toxicity information with the HTS and genomic data of ToxCast within the ACToR system.
This map, by default, contains heuristics to instantiate additional VMs when the actor system has insufficient resource, to terminate VMs when there are excessive resources for a significant period and a series of heuristics to increase and reduce actor instantiations according to demand.
All of the data for this analysis are collected in the ACToR system (Judson et al. 2008; U.S. EPA 2008a).
The data we describe here are a subset of those contained in the ACToR system being developed at the U.S. EPA to manage large collections of data on environmental chemicals.
Indeed, the fact that execution within an actor is sequential prevents certain actor systems to take advantage of multicore architectures.
As a result, some interaction between subsets of intentions and actor systems will lead to unexpected results at lower levels.
We take all that a step further with the application of actor systems as an appropriate theoretical model for fine-grained, yet simplified and practical, monitoring of massive sets of SLAs.
Historical evidence of such behaviour in a multiple-actor system is the European BoP system of the 19th and early 20th centuries, although the fatality of such miscalculations in a nuclear-backed system can definitely be seen as an additional restraining factor.
This multidimensionality comprises different strategies depending on types of actors, system levels, contextual factors, program progress over time, program content, types of learning and change processes, and the conditions for sustainability.
