On The Study Of Human Cooperation Via Computer Simulation

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.

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.

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 book brings together philosophical approaches to cooperation and collective agency with research into human-machine interaction and cooperation from engineering, robotics, computer science and AI. Bringing these so far largely unrelated fields of study together leads to a better understanding of collective agency in natural and artificial systems and will help to improve the design and performance of hybrid systems involving human and artificial agents. Modeling collective agency with the help of computer simulations promises also philosophical insights into the emergence of collective agency. The volume consists of four sections. The first section is dedicated to the concept of agency. The second section of the book turns to human-machine cooperation. The focus of the third section is the transition from cooperation to collective agency. The last section concerns the explanatory value of social simulations of collective agency in the broader framework of cultural evolution.

Research on general video game playing aims at designing agents or content generators that can perform well in multiple video games, possibly without knowing the game in advance and with little to no specific domain knowledge. The general video game AI framework and competition propose a challenge in which researchers can test their favorite AI methods with a potentially infinite number of games created using the Video Game Description Language. The open-source framework has been used since 2014 for running a challenge. Competitors around the globe submit their best approaches that aim to generalize well across games. Additionally, the framework has been used in AI modules by many higher-education institutions as assignments, or as proposed projects for final year (undergraduate and Master's) students and Ph.D. candidates. The present book, written by the developers and organizers of the framework, presents the most interesting highlights of the research performed by the authors during these years in this domain. It showcases work on methods to play the games, generators of content, and video game optimization. It also outlines potential further work in an area that offers multiple research directions for the future.

Games, whether educational or recreational, are meant to be fun. How do we ensure that the game delivers its intent? The answer to this question is playtesting. However, a haphazard playtest process cannot discover play experience from various dimensions. Players' perceptions, affordances, age, gender, culture, and many more human factors influence play experience. A playtest requires an intensive experimental process and scientific protocols to ensure that the outcomes seen are reliable for the designer. Playtesting and players' affordances are the focus of this book. This book is not just about the playtest procedures but also demonstrates how they lead to the conclusions obtained when considering data sets. The playtest process or playtest stories differ according to the hypothesis under investigation. We cover examples of playtesting to identify the impact of human factors, such as age and gender, to examine a player's preferences for game objects' design and colors. The book details topics to reflect on possible emotional outcomes of the player at the early stages of game design as well as the methodology for presenting questions to players in such a way as to elicit authentic feedback. This book is intended mainly for game designers, researchers, and developers. However, it provides a general understanding of affordances and human factors that can be informative for readers working in any domain.

Technological development has changed the nature of industrial production so that it is no longer a question of humans working with a machine, but rather that a joint human machine system is performing the task. This development, which started in the 1940s, has become even more pronounced with the proliferation of computers and the invasion of digital technology in all wakes of working life. It may appear that the importance of human work has been reduced compared to what can be achieved by intelligent software systems, but in reality, the opposite is true: the more complex a system, the more vital the human operator's task. The conditions have changed, however, whereas people used to be in control of their own tasks, today they have become supervisors of tasks which are shared between humans and machines. A considerable effort has been devoted to the domain of administrative and clerical work and has led to the establishment of an internationally based human-computer interaction (HCI) community at research and application levels. The HCI community, however, has paid more attention to static environments where the human operator is in complete control of the situation, rather than to dynamic environments where changes may occur independent of human intervention and actions. This book's basic philosophy is the conviction that human operators remain the unchallenged experts even in the worst cases where their working conditions have been impoverished by senseless automation. They maintain this advantage due to their ability to learn and build up a high level of expertise -- a foundation of operational knowledge -- during their work. This expertise must be taken into account in the development of efficient human-machine systems, in the specification of training requirements, and in the identification of needs for specific computer support to human actions. Supporting this philosophy, this volume *deals with the main features of cognition in dynamic environments, combining issues coming from empirical approaches of human cognition and cognitive simulation, *addresses the question of the development of competence and expertise, and *proposes ways to take up the main challenge in this domain -- the design of an actual cooperation between human experts and computers of the next century.