Computer Simulation Of Human Behavior

This book, originally published in 1970, concerns the new technique of computer simulation in psychology at the time. Computer programs described include models of learning, problem-solving, pattern recognition, the use of language, and personality. More general topics are discussed including the evaluation of such models, the relation of the field to cybernetics, and the problem posed by consciousness. Today it can be read and enjoyed in its historical context.

Cooperation is pervasive throughout nature, but its origin remains an open question. For decades, social scientists, business leaders, and economists have struggled with an important question: why is cooperation so ubiquitous among unrelated humans? The answers would have profound effects because anything that promotes cooperation leads to more productive work environments and benefits society at large. Game theory provides an ideal framework for studying social dilemmas, or those situations in which people decide whether to cooperate with others (benefitting the group) or defect by prioritizing their self-interest (benefitting only the individual). The social dilemma is formulated as a mathematical game and then programmed into a computer model. Simulating the game allows researchers to investigate potential theories to explain how cooperation emerges and what promotes its persistence. Over the past 25 years, countless papers on social dilemma games have been published, yet arguably little progress has been made. The problem is the social dilemma game models are unrealistic in the sense they contain artificial constructs that deviate from the way humans act. This book describes the shortcomings in current social dilemma game modeling techniques and provides guidance on designing more effective models. A basic introduction to game theory is provided with an emphasis on the prisoner's dilemma, the most widely studied social dilemma game. Individual chapters are provided detailing the shortcomings of weak selection, spatial games, and the Moran process. Computer model validation is also discussed at length. The recommendations found in this book should help design more realistic social dilemma game models likely to produce a better understanding of human cooperation.

This dissertation describes a computer simulation model of paranoia. The model mimics the behavior of a patient participating in a psychiatric interview by answering questions, introducing its own topics, and responding to negatively-valued (e. g., threatening or shame-producing) situations. The work focuses on the motivational mechanisms required to instigate and direct the modelled behavior. Major components of the model are: (1) A production system (PS) formalism accounting for the instigation and guidance of behavior as a function of internal (affective) and external (real-word) environmental factors; (2) A model of affects (emotions) as an anticipation mechanism based on a small number of basic pain-pleasure factors; and (3) a formalism for intensional behavior (directed by internal models) requiring a dual representation of symbol and concept. An intensional object (belief) can be accessed either by sensing it in the environment (concept) or by its name (token). Similarly, an intensional action (intention) can be specified either by its conditions in the immediate environment (concept) or by its name (token). Issues of intelligence, psychopathological modelling, and artificial intelligence programming are discussed. The paranoid phenomenon is found to be explainable as an extremely skewed use of normal processes. Applications of these constructs are found to be useful in AI programs dealing with error recovery, incompletely specified input data, and natural language specification of tasks to perform.

Understanding human behavior is generally a difficult task because of the complexity of the individual (or the group of individuals) that is subjected to intertwined factors, forces, values, and other motivational resources that are influencing behavior. A qualitative model of the individual was developed to account for the factors and forces exerted on the individual and the individual’s goals. Personal behavior was further modeled by a vector with a magnitude and a direction. The magnitude depends on factors and forces that may be unleveraged or leveraged. The direction of the behavior vector represents the goals of the individual. The behavior model was extended to a group of individuals by considering a group vector. The role of past experience and resources supporting and influencing the indivual and the group were identified and discussed. Decision processes for the individual and the group were developed since it is through decisions that behavior is developed and adopted. The model also includes immutable factors to guide the individual toward a task-oriented or relationship-oriented human behavior. An error process was also developed to identify and correct errors so that the decisions taken are accurate, complete, and uptodate. Several illustrative applications of the human behavior model are presented and discussed. These applications relate to the individual and the group with specific goals and in particular situations.