John H. Holland outlines a theory of adaptive systems that integrates concepts from biology, genetics, and automata theory. The theory is structured into five main sections, focusing on the study of adaptation through generation procedures, the definition of a continuum of generation procedures, the realization of these procedures in iterative circuit computers, the process of adaptation, and the nature of the theory's theorems. The theory distinguishes between "complete" and "incomplete" models, where "complete" models are artificial systems with fully defined properties, and "incomplete" models represent natural systems with complex, unbounded variables. The theory uses "universal generation procedures" that can produce any program of a universal computer, and it emphasizes the role of connection and disconnection probabilities in controlling the generation process. The theory introduces a model where generation procedures are represented by a set of generators and a generation tree, with each node representing a program. The generation tree allows for the combination of generators to form new programs, and the connection and disconnection probabilities determine the density of programs over time. The theory also discusses the use of templates to modify generation procedures, enabling the adaptation of supervisory programs to optimize problem-solving. The environment is treated as a population of problems, and the adaptive system interacts with this environment by generating and modifying programs to solve these problems. The theory emphasizes the importance of activation, a measure of success in solving problems, which is released to the supervisory program when a solution is found. The process of adaptation involves the differential selection of supervisory programs based on their effectiveness in solving problems. The theory also explores the use of iterative circuit computers to model generation procedures, where modules are arranged in a regular array and interact based on predefined rules. The theory discusses the properties of these computers, including their ability to simulate various types of automata and the role of relative addressing in locating operands. The theory concludes that the use of templates allows for flexible control over the generation procedure, enabling the adaptive system to evolve and improve its problem-solving capabilities.John H. Holland outlines a theory of adaptive systems that integrates concepts from biology, genetics, and automata theory. The theory is structured into five main sections, focusing on the study of adaptation through generation procedures, the definition of a continuum of generation procedures, the realization of these procedures in iterative circuit computers, the process of adaptation, and the nature of the theory's theorems. The theory distinguishes between "complete" and "incomplete" models, where "complete" models are artificial systems with fully defined properties, and "incomplete" models represent natural systems with complex, unbounded variables. The theory uses "universal generation procedures" that can produce any program of a universal computer, and it emphasizes the role of connection and disconnection probabilities in controlling the generation process. The theory introduces a model where generation procedures are represented by a set of generators and a generation tree, with each node representing a program. The generation tree allows for the combination of generators to form new programs, and the connection and disconnection probabilities determine the density of programs over time. The theory also discusses the use of templates to modify generation procedures, enabling the adaptation of supervisory programs to optimize problem-solving. The environment is treated as a population of problems, and the adaptive system interacts with this environment by generating and modifying programs to solve these problems. The theory emphasizes the importance of activation, a measure of success in solving problems, which is released to the supervisory program when a solution is found. The process of adaptation involves the differential selection of supervisory programs based on their effectiveness in solving problems. The theory also explores the use of iterative circuit computers to model generation procedures, where modules are arranged in a regular array and interact based on predefined rules. The theory discusses the properties of these computers, including their ability to simulate various types of automata and the role of relative addressing in locating operands. The theory concludes that the use of templates allows for flexible control over the generation procedure, enabling the adaptive system to evolve and improve its problem-solving capabilities.