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Can we understand important social issues by studying individual personalities and decisions? Or are societies somehow more than the people in them? Sociologists have long believed that psychology can't explain what happens when people work together in complex modern societies. In contrast, most psychologists and economists believe that if we have an accurate theory of how individuals make choices and act on them, we can explain pretty much everything about social life. Social Emergence takes a new approach to these longstanding questions. Sawyer argues that societies are complex dynamical systems, and that the best way to resolve these debates is by developing the concept of emergence, focusing on multiple levels of analysis - individuals, interactions, and groups - and with a dynamic focus on how social group phenomena emerge from communication processes among individual members. This book makes a unique contribution not only to complex systems research but also to social theory.
Autonomy is a characterizing notion of agents, and intuitively it is rather unambiguous. The quality of autonomy is recognized when it is perceived or experienced, yet it is difficult to limit autonomy in a definition. The desire to build agents that exhibit a satisfactory quality of autonomy includes agents that have a long life, are highly independent, can harmonize their goals and actions with humans and other agents, and are generally socially adept. Agent Autonomy is a collection of papers from leading international researchers that approximate human intuition, dispel false attributions, and point the way to scholarly thinking about autonomy. A wide array of issues about sharing control and initiative between humans and machines, as well as issues about peer level agent interaction, are addressed.
Invited papers; knowledge representation and automated reasoning; tutoring systems; machine learning; neural networks; distributed AI; knowledge acquisition and knowledge bases; posters.
Agent-based modelling on a computer appears to have a special role to play in the development of social science. It offers a means of discovering general and applicable social theory, and grounding it in precise assumptions and derivations, whilst addressing those elements of individual cognition that are central to human society. However, there are important questions to be asked and difficulties to overcome in achieving this potential. What differentiates agent-based modelling from traditional computer modelling? Which model types should be used under which circumstances? If it is appropriate to use a complex model, how can it be validated? Is social simulation research to adopt a realist ...
Multi-Agent Programming is an essential reference for anyone interested in the most up-to-date developments in MAS programming. While previous research has focused on the development of formal and informal approaches to analyze and specify Multi-Agent Systems, this book focuses on the development of programming languages and tools which not only support MAS programming, but also implement key concepts of MAS in a unified framework. Part I describes approaches that rely on computational logic or process algebra – Jason, 3APL, IMPACT, and CLAIM/SyMPA. Part II presents languages and platforms that extend or are based on Java – JADE, Jadex and JACKTM. Part III provides two significant industry specific applications – The DEFACTO System for coordinating human-agent teams for disaster response, and the ARTIMIS rational dialogue agent technology. Also featured are seven appendices for quick reference and comparison.
This book offers a widely interdisciplinary approach to investigating important questions surrounding the cognitive foundations of group attitudes and social interaction. The volume tackles issues such as the relationship between individual and group attitudes, the cognitive bases of group identity and group identification and the link between emotions and individual attitudes. This volume delves into the links between individual attitudes (such as beliefs, goals and intentions) and how they are reflected in shared attitudes where common belief, collective acceptance, joint intentions, and group preferences come into play. It pursues answers to the connections between trust and beliefs, goal...
This volume provides a selection of strictly refereed papers first presented during a workshop held within the context of the ESPRIT ModelAge Project in Certosa di Pertignano, Italy, in 1997. The 15 revised full papers presented together with an introductory survey by the volume editors were carefully reviewed for inclusion in the book. The book is devoted to the interdisciplinary study of formal models of agency and intelligent agents from the points of view of artificial intelligence, software engineering, applied logic, databases, and organization theory. Among the topics addressed are various types of agents and multi-agent systems, cooperation, communication, specification, verification, deontic logic, diagnosis, and decision making.
This volume presents revised versions of the papers presented at the 4th International Workshop on Multi-agent Based Simulation (MABS 2003), a workshop federated with the2ndInternationalJointConferenceonAutonomousAgentsandMulti-agentSystems (AAMAS 2003), which was held in Melbourne, Australia, in July 2003. In addition to the papers presented at the workshop, three additional papers have been included in this volume (Robertson, Noto et al., and Marietto et al.). Multiagent Based Simulation (MABS) is a vibrant interdisciplinary area which brings together researchers active within the agent-based social simulation community (ABSS) and the multiagent systems community (MAS). These two communities have different, indeed somewhat divergent, goals. The focus of ABSS is on simulating and synthesizing social behaviors in order to understand observed social systems (human, animal and even electronic) via the development and testing of new models and c- cepts. MAS focuses instead on the solution of hard engineering problems related to the construction, deployment and ef?cient operation of multiagent-based systems.
From the 1970s to the new millennium, the prison population in the United States has quadrupled while an unprecedented amount of sentencing reform has taken place, largely intended to protect the public from dangerous criminals. This book details the California experience, including the history and politics of criminal sentencing policy reform, as well as the consequences of this activity to the criminal justice system. Using cutting-edge computer simulation modeling, Kathleen Auerhahn explores the impact that sentencing reforms dating back to the 1970s have had on the composition and structure of the criminal justice system, with specific focus on prison populations. She illustrates how dynamic systems simulation modeling is used to both examine "possible futures" under a variety of sentencing structures and sentencing policy alternatives, including narrowing "strike zones" and the early release of elderly offenders, in order to more effectively target the dangerous criminals these policies promise to remove from society via incarceration.
The question of how cooperation and social order can evolve from a Hobbesian state of nature of a “war of all against all” has always been at the core of social scientific inquiry. Social dilemmas are the main analytical paradigm used by social scientists to explain competition, cooperation, and conflict in human groups. The formal analysis of social dilemmas allows for identifying the conditions under which cooperation evolves or unravels. This knowledge informs the design of institutions that promote cooperative behavior. Yet to gain practical relevance in policymaking and institutional design, predictions derived from the analysis of social dilemmas must be put to an empirical test. T...