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Plan, Activity, and Intent Recognition
Plan recognition, activity recognition, and intent recognition together combine and unify techniques from user modeling, machine vision, intelligent user interfaces, human/computer interaction, autonomous and multi-agent systems, natural language understanding, and machine learning. Plan, Activity, and Intent Recognition explains the crucial role of these techniques in a wide variety of applications including: - personal agent assistants - computer and network security - opponent modeling in games and simulation systems - coordination in robots and software agents - web e-commerce and collaborative filtering - dialog modeling - video surveillance - smart homes In this book, follow the histor...
Social Interactions in Virtual Worlds
This cross-disciplinary exploration of MMOs and other complex online worlds melds work from computer science, psychology and social science.
Computational Theory of Mind for Human-Machine Teams
This book constitutes the proceedings of the First International Symposium, ToM for Teams 2021, held in Washington, DC, USA, during November 4–6, 2021, Each chapter in this section tackles a different aspect of AI representing the thoughts and beliefs of human agents. The work presented herein represents our collective efforts to better understand ToM, develop AI with ToM capabilities (ASI), and study how to integrate such systems into human teams.
Social-Behavioral Modeling for Complex Systems
This volume describes frontiers in social-behavioral modeling for contexts as diverse as national security, health, and on-line social gaming. Recent scientific and technological advances have created exciting opportunities for such improvements. However, the book also identifies crucial scientific, ethical, and cultural challenges to be met if social-behavioral modeling is to achieve its potential. Doing so will require new methods, data sources, and technology. The volume discusses these, including those needed to achieve and maintain high standards of ethics and privacy. The result should be a new generation of modeling that will advance science and, separately, aid decision-making on maj...
Social, Cultural, and Behavioral Modeling
This book constitutes the refereed proceedings of the 10th International Conference on Social, Cultural, and Behavioral Modeling & Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2017, held in Washington, DC, USA, in July 2017. The 16 full papers and 27 short papers presented were carefully reviewed and selected from 79 submissions. Owing to its strong multi-disciplinary heritage, the papers represent a large range of disciplines including computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science and use numerous types of computational methods such as machine learning, language technology, social network analysis and visualization, agent-based simulation, and statistics. They are organized in the following topical sections: behavioral and social sciences; cyber and intelligence applications; information, systems, and network sciences; and methodology.
Theories of Team Cognition
Cognitive processes in teams have been a valuable arena for team researchers to explore. Team cognition research advances and informs a variety of disciplines, including cognitive and social sciences, engineering, military science, organizational science, human factors, medicine, and communications. There has been a great deal of progress in the team cognition literature, yet the field is still in its early stages of maturity. There is much more to be gained from the field’s insights and there is a need to unite the diverse array of scholarly ideas that permeate the field. This movement will serve to organize the research and ideas that have surfaced in the field, thereby making them more accessible to different disciplines while at the same time, motivating continued progress in the field. This book aims to be a step in this direction and acts as a forum for leading scholars to share their ideas, theories, models, and conceptions about what matters and where more attention is needed in the field of team cognition.
Massive Graph Analytics
"Graphs. Such a simple idea. Map a problem onto a graph then solve it by searching over the graph or by exploring the structure of the graph. What could be easier? Turns out, however, that working with graphs is a vast and complex field. Keeping up is challenging. To help keep up, you just need an editor who knows most people working with graphs, and have that editor gather nearly 70 researchers to summarize their work with graphs. The result is the book Massive Graph Analytics." — Timothy G. Mattson, Senior Principal Engineer, Intel Corp Expertise in massive-scale graph analytics is key for solving real-world grand challenges from healthcare to sustainability to detecting insider threats, cyber defense, and more. This book provides a comprehensive introduction to massive graph analytics, featuring contributions from thought leaders across academia, industry, and government. Massive Graph Analytics will be beneficial to students, researchers, and practitioners in academia, national laboratories, and industry who wish to learn about the state-of-the-art algorithms, models, frameworks, and software in massive-scale graph analytics.
Social, Cultural, and Behavioral Modeling
This book constitutes the refereed proceedings of the 9th International Conference on Social, Cultural, and Behavioral Modeling & Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2016, held in Washington, DC, USA, in June/July 2016. The 38 full papers presented were carefully reviewed and selected from 78 submissions. The goal of this conference was to build a new community of social cyber scholars by bringing together and fostering interaction between members of the scientific, corporate, government and military communities interested in understanding, forecasting and impacting human socio-cultural behavior. For this three challenges have to be met: deep understanding, socio-cognitive reasoning, and re-usable computational technology. Thus papers come from a wide number of disciplines: computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science.
Ethics of Artificial Intelligence
Should a self-driving car prioritize the lives of the passengers over the lives of pedestrians? Should we as a society develop autonomous weapon systems that are capable of identifying and attacking a target without human intervention? What happens when AIs become smarter and more capable than us? Could they have greater than human moral status? Can we prevent superintelligent AIs from harming us or causing our extinction? At a critical time in this fast-moving debate, thirty leading academics and researchers at the forefront of AI technology development come together to explore these existential questions, including Aaron James (UC Irvine), Allan Dafoe (Oxford), Andrea Loreggia (Padova), Andrew Critch (UC Berkeley), Azim Shariff (Univ. .
Artificial General Intelligence
This book constitutes the refereed proceedings of the 17th International Conference on Artificial General Intelligence, AGI 2024, held in Seattle, Washington, USA in August 2024. The 25 papers presented in this book were carefully reviewed and selected from 55 submissions. The papers focus on the main theme of AGI 2024: 'Understanding Artificial General Intelligence', with discussions on various central concepts of general intelligence including thought, understanding, meaning, creativity, insight, reasoning, autonomy, attention and control.
