Abstract This paper presents a modular design approach for the implementation of process‐oriented or event‐oriented discrete systems simulation software. Requirements for such a simulation facility are discussed, to include list processing capabilities, data structuring capabilities, dynamic allocation of data storage, statistics collection and number‐crunching capabilities, and subprograms. Specific focus is placed upon implementing the process view which requires constructs in the language for initiating, controlling and terminating a process. Resource management facilities are also considered, to include a means of defining a resource with its associated resource handler and a set of primitives for requesting, releasing and obtaining status information regarding a resource. HPSIM, an organized collection of modules written in Modula‐2, was designed to facilitate both event‐oriented and process‐oriented discrete systems simulation, Modula‐2 was chosen for its data abstraction facilities, its software engineering capabilities, its execution efficiency, its ability for separate compilation and its implementation of co‐routines. The modeller encapsulates the conceptual model of the system into a software module which is interfaced with the HPSIM modules. The IMPORT statement in Modula‐2 allows the modeller to access any of the routines provided by HPSIM as required. An example involving a single‐server CPU system highlights the process/resource features of HPSIM.

Abstract This series of articles describes research which has been underway at The Ohio State University in an effort to develop a fundamental and general theory of information flow and analysis. More specifically, the research attempts to (1) identify and quantify important variables and parameters in the information flow process; (2) establish relationships among these variables; (3) apply the theory to practical situations and to examine the resulting implications; and (4) develop models, both simulation and experimental, to utilize and validate the theory. The basis for our work treats information as data of value in decision‐making. This, in turn, leads to a powerful model of a Generalized Information System. We have now made considerable progress and have developed the basic elements comprising a generalized theory. In particular, we have been able to establish quantitative definitions for and relationships among: quantity of information, value of information, effectiveness of information, decision‐maker effectiveness, decision‐maker performance, and other terms. By dealing with “average” decision‐makers, we establish unique relationships for specific decision situations. Typical relationships and curves are presented in the articles. We describe a flexible, sophisticated simulation model which permits the examination of the interrelationship between information and decision‐making for a wide variety of different situations. We present detailed simulation results for two specific examples‐a typical farmer and a mathematical example. We describe prototype experiments which place human decision‐makers in an interactive decision‐making situation. We are able to obtain data on their decision‐making behavior in the light of our conceptual model. Preliminary analysis of the data is described.

Abstract This series of articles describes research which has been underway at The Ohio State University in an effort to develop a fundamental and general theory of information flow and analysis. More specifically, the research attempts to (1) identify and quantify important variables and parameters in the information flow process; (2) establish relationships among these variables; (3) apply the theory to practical situations and to examine the resulting implications; and (4) develop models, both simulation and experimental, to utilize and validate the theory. The basis for our work treats information as data of value in decision‐making. This, in turn, leads to a powerful model of a Generalized Information System. We have now made considerable progress and have developed the basic elements comprising a generalized theory. In particular, we have been able to establish quantitative definitions for and relationships among quantity of information, value of information, effectiveness of information, decision‐maker effectiveness, decision‐maker performance, and other terms. By dealing with “average” decision‐makers, we establish unique relationships for specific decision situations. Typical relationships and curves are presented in the articles. We describe a flexible, sophisticated simulation model which permits the examination of the interrelationship between information and decision‐making for a wide variety of different situations. We present detailed simulation results for two specific examples‐a typical farmer and a mathematical example. We describe prototype experiments which place human decision‐makers in an interactive decision‐making situation. We are able to obtain data on their decision‐making behavior in the light of our conceptual model. Preliminary analysis of the data is described.

Abstract This series of articles describes research which has been underway at The Ohio State University in an effort to develop a fundamental and general theory of information flow and analysis. More specifically, the research attempts to (1) identify and quantify important variables and parameters in the information flow process; (2) establish relationships among these variables; (3) apply the theory to practical situations and to examine the resulting implications; and (4) develop models, both simulation and experimental, to utilize and validate the theory. The basis for our work treats information as data of value in decision‐making. This, in turn, leads to a powerful model of a Generalized Information System. We have now made considerable progress and have developed the basic elements comprising a generalized theory. In particular, we have been able to establish quantitative definitions for and relationships among quantity of information, value of information, effectiveness of information, decision‐maker effectiveness, decision‐maker performance, and other terms. By dealing with “average” decision‐makers, we establish unique relationships for specific decision situations. Typical relationships and curves are presented in the articles. We describe a flexible, sophisticated simulation model which permits the examination of the interrelationship between information and decision‐making for a wide variety of different situations. We present detailed simulation results for two specific examples—a typical farmer and a mathematical example. We describe prototype experiments which place human decision‐makers in an interactive decision‐making situation. We are able to obtain data on their decision‐making behavior in the light of our conceptual model. Preliminary analysis of the data is described.

Many languages, including Fortran, and machines such as most minicomputers have little or no built-in character manipulation capability and yet are often required to process character information. This paper discusses the programming of character processing in such integer environments. Character representation, string-to-word coordinate transformation, packing, and unpacking using several arithmetic schemes are discussed with special attention to program portability. Several Fortran subroutines are presented culminating in BYTRAN, a set of portable Fortran subroutines that simulate the string structures and operators of the PL/I language.