In computer science, the Actor model, first published in 1973, is a mathematical model of concurrent computation.
A fundamental challenge in defining the Actor model is that it did not provide for global states so that a computational step could not be defined as going from one global state to the next global state as had been done in all previous models of computation.
In 1963 in the field of Artificial Intelligence, John McCarthy introduced situation variables in logic in the Situational Calculus. In McCarthy and Hayes 1969, a situation is defined as "the complete state of the universe at an instant of time." In this respect, the situations of McCarthy are not suitable for use in the Actor model since it has no global states.
From the definition of an Actor, it can be seen that numerous events take place: local decisions, creating Actors, sending messages, receiving messages, and designating how to respond to the next message received. Partial orderings on such events have been axiomatized in the Actor model and their relationship to physics explored (see Actor model theory).
According to Hewitt (2006), the Actor model is based on physics in contrast with other models of computation that were based on mathematical logic, set theory, algebra, etc. Physics influenced the Actor model in many ways, especially quantum physics and relativistic physics. One issue is what can be observed about Actor systems. The question does not have an obvious answer because it poses both theoretical and observational challenges similar to those that had arisen in constructing the foundations of quantum physics. In concrete terms for Actor systems, typically we cannot observe the details by which the arrival order of messages for an Actor is determined (see Indeterminacy in concurrent computation). Attempting to do so affects the results and can even push the indeterminacy elsewhere. e.g., see metastability in electronics. Instead of observing the insides of arbitration processes of Actor computations, we await the outcomes.