This paper, authored by Carl Hewitt, discusses the Actor Model of Computation and its application to understanding control structures as patterns of passing messages. The Actor Model is a communication-based approach to modeling intelligent systems, where actors interact by sending messages to each other. The paper outlines the methodology for modeling intelligent individuals and societies of experts, emphasizing the importance of reciprocal communication and explicit knowledge representation. It introduces the Actor Model, which consists of actors, their actions, and their acquaintances (other actors they know about). The paper also details the Actor Transmission mechanism, which allows actors to integrate information from different sources. The paper then explores how control structures, such as iteration and recursion, can be understood through the Actor Model. It uses event diagrams to illustrate the internal structure of computations, showing how these control structures are patterns of message passing. For example, recursion is characterized by a chain of continuation actors, each knowing only about the next actor in the chain, which eventually replies with the result. The paper also discusses the efficiency and intelligibility of Actor-based systems, highlighting the modular distribution of knowledge and the elimination of "hairy control structures" (such as possibility lists and non-local gotos). It provides examples of how Actor-based systems can be more structured and intuitive, and how they can be refined to achieve efficient implementations. Overall, the paper aims to provide a framework for understanding and characterizing control structures in terms of message passing, laying the groundwork for further exploration of parallelism and communication within the Actor Model.This paper, authored by Carl Hewitt, discusses the Actor Model of Computation and its application to understanding control structures as patterns of passing messages. The Actor Model is a communication-based approach to modeling intelligent systems, where actors interact by sending messages to each other. The paper outlines the methodology for modeling intelligent individuals and societies of experts, emphasizing the importance of reciprocal communication and explicit knowledge representation. It introduces the Actor Model, which consists of actors, their actions, and their acquaintances (other actors they know about). The paper also details the Actor Transmission mechanism, which allows actors to integrate information from different sources. The paper then explores how control structures, such as iteration and recursion, can be understood through the Actor Model. It uses event diagrams to illustrate the internal structure of computations, showing how these control structures are patterns of message passing. For example, recursion is characterized by a chain of continuation actors, each knowing only about the next actor in the chain, which eventually replies with the result. The paper also discusses the efficiency and intelligibility of Actor-based systems, highlighting the modular distribution of knowledge and the elimination of "hairy control structures" (such as possibility lists and non-local gotos). It provides examples of how Actor-based systems can be more structured and intuitive, and how they can be refined to achieve efficient implementations. Overall, the paper aims to provide a framework for understanding and characterizing control structures in terms of message passing, laying the groundwork for further exploration of parallelism and communication within the Actor Model.