References on the Actor Programming Model
The actor programming model is a software development method that encourages the decomposition of applications into autonomous components which are self-contained and operate asynchronously and independently from one another. This model is well aligned with the nondeterministic nature of distributed systems, including mobile systems, interactive systems, and the internet.
As I mentioned previously, I didn’t invent it. I’m merely leveraging the information obtained from a number of sources and applying it in a way that I think makes it easier to build certain types of applications. Applications that can benefit from a highly concurrent actor-based programming model include reactive systems — ones that respond to nondeterministic external events. Since many applications can be described as “a program that responds to external events” it only makes sense that the actor programming model can be applied to many domains.
Here are some papers that I’ve read on the actor model, some of which have influenced me in how I think about concurrent programming and others that have merely provided background information or depicted ways in which concurrent programming should not be approached.
Actors, Rajesh K. Karmani, Gul Agha
Actors: A Model of Concurrent Computation In Distributed Systems, Gul A. Agha (out of print)
Actor Languages for Specification of Parallel Computations, Gul Agha, Wooyoung Kim, Rajendra Panwar
An Actor-Based Framework for Heterogeneous Computing Systems, Gul Agha, Rajendra Panwar
Actors that Unify Threads and Events, Philipp Haller, Martin Odersky
Compilation of a Highly Parallel Actor-Based Language, WooYoung Kim, Gul Agha
These are some of the more involved works from which I’ve found many useful bits of information. I’ve got them permanently stored in GoodReader so I can keep looking back to them (and my associated annotations as well). Hopefully anyone looking to build systems using the actor model (and hopefully, using Stact if you’re on the .NET platform) can get a better understanding of the model by reviewing these papers.