A Mixed-initiative Framework for Multi-agent Human-robot Teams PDF Download

Author: John Alexander Duncan
Publisher:
ISBN:
Category :
Languages : en
Pages : 310

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Book Description
Robots and autonomous systems are expanding into more complex, dynamic, and human-centered operating domains. In such domains, neither full autonomy nor full human control are ideal and the appropriate level of autonomy is contextually-dependent. Mixed-initiative systems enable flexible autonomy, making them ideal for complex operating environments. However, most mixed-initiative research does not consider multi-agent human-robot systems, and a multi-agent mixed-initiative robot control framework is not readily available. This project explores the requirements for a mixed-initiative human-robot control framework and proposes an initial design. The mixed-initiative framework was deployed onto a mobile robot, where three different agents could take, transfer, share, enable, or disable robot control. Compared to single-agent systems, the multi-agent mixed-initiative system completed a series of navigation tasks more quickly. The multi-agent system also completed navigation tasks that a single-agent autonomous system could not. Further design improvements and applications for mixed-initiative systems are discussed

Author: Francien Dechesne
Publisher: Springer Science & Business Media
ISBN: 3642272150
Category : Business & Economics
Languages : en
Pages : 525

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Book Description
This book constitutes the thoroughly refereed post-workshop proceedings of 5 workshops, held at the 10th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2011, in Taipei, Taiwan, May 2-6, 2011. The 37 revised full papers presented together with 1 invited paper were carefully reviewed and selected from numerous submissions. The papers are organized in sections on the workshops Agent-Based Modeling for Policy Engineering (AMPLE), Agent-Oriented Software Engineering (AOSE), Autonomous Robots and Multirobot Systems (ARMS), Data Oriented Constructive Mining and Multi-Agent Simulation, Massively Multi-Agent Systems: Models, Methods and Tools (DOCM3AS), and Infrastructures and Tools for Multiagent Systems (ITMAS).

Author: Matthew T. Long
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description
ABSTRACT: Heterogeneous multi-agent systems are currently used in a wide variety of situations, including search and rescue, military applications, and off-world exploration, however it is difficult to understand the actions of these systems or naturalistically assign these mixed teams to tasks. These agents, which may be human, robot or software, have different capabilities but will need to coordinate effectively with humans in order to operate. The first and largest contributing factor to this challenge is the processing, understanding and representing of elements of the natural world in a manner that can be utilized by artificial agents. A second contributing factor is that current abstractions and robot architectures are ill-suited to address this problem. This dissertation addresses the lack of a high-level abstraction for the naturalistic coordination of teams of heterogeneous robots, humans and other agents through the development of roles. Roles are a fundamental concept of social science that may provide this necessary abstraction. Roles are not a new concept and have been used in a number of related areas. This work draws from these fields and constructs a coherent and usable model of roles for robotics. This research is focussed on answering the following question: Can the use of social roles enable the naturalistic coordinated operation of robots in a mixed setting? In addition to this primary question, related research includes defining the key concepts important to artificial systems, providing a mapping and implementation from these concepts to a usable robot framework and identifies a set of robot-specific roles used for human-robot interaction. This research will benefit both the artificial intelligence agent and robotics communities. It poses a fundamental contribution to the multi-agent community because it extends and refines the role concept. The application of roles in a principled and complete implementation is a novel contribution to both software and robotic agents. The creation of an open source operational architecture which supports taskable robots is also a major contribution.

Author: Barbara Dunin-Keplicz
Publisher: John Wiley & Sons
ISBN: 1119957605
Category : Technology & Engineering
Languages : en
Pages : 244

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Book Description
What makes teamwork tick? Cooperation matters, in daily life and in complex applications. After all, many tasks need more than a single agent to be effectively performed. Therefore, teamwork rules! Teams are social groups of agents dedicated to the fulfilment of particular persistent tasks. In modern multiagent environments, heterogeneous teams often consist of autonomous software agents, various types of robots and human beings. Teamwork in Multi-agent Systems: A Formal Approach explains teamwork rules in terms of agents' attitudes and their complex interplay. It provides the first comprehensive logical theory, TeamLog, underpinning teamwork in dynamic environments. The authors justify design choices by showing TeamLog in action. The book guides the reader through a fascinating discussion of issues essential for teamwork to be successful: What is teamwork, and how can a logical view of it help in designing teams of agents? What is the role of agents' awareness in an uncertain, dynamic environment? How does collective intention constitute a team? How are plan-based collective commitments related to team action? How can one tune collective commitment to the team's organizational structure and its communication abilities? What are the methodological underpinnings for teamwork in a dynamic environment? How does a team and its attitudes adjust to changing circumstances? How do collective intentions and collective commitments arise through dialogue? What is the computational complexity of TeamLog? How can one make TeamLog efficient in applications? This book is an invaluable resource for researchers and graduate students in computer science and artificial intelligence as well as for developers of multi-agent systems. Students and researchers in organizational science, in particular those investigating teamwork, will also find this book insightful. Since the authors made an effort to introduce TeamLog as a conceptual model of teamwork, understanding most of the book requires solely a basic logical background.

Author: Dignum, Virginia
Publisher: IGI Global
ISBN: 1605662577
Category : Technology & Engineering
Languages : en
Pages : 630

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Book Description
"This book provide a comprehensive view of current developments in agent organizations as a paradigm for both the modeling of human organizations, and for designing effective artificial organizations"--Provided by publisher.

Author: Steven James Levine
Publisher:
ISBN:
Category :
Languages : en
Pages : 378

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Book Description
There is an ever-growing demand for humans and robots to work fluidly together in a number of important domains, such as home care, manufacturing, and medical robotics. In order to achieve this fluidity, robots must be able to (1) recognize their human teammate’s intentions, and (2) automatically adapt to those intentions in an intelligent manner. This thesis makes progress in these areas by proposing a framework that solves these two problems (task-level intent recognition and robotic adaptation) concurrently and holistically, using a single model and set of algorithms for both. The result is a mixed-initiative human-robot interaction that achieves the team’s goals. The robot is able to reason about the action requirements, timing constraints, and unexpected disturbances in order to adapt intelligently to the human. We extend this framework by additionally maintaining a probabilistic belief over the human’s intentions. We develop a risk-aware executive that performs concurrent intent recognition and adaptation. Our executive continuously assesses the risk associated with plan execution, selects adaptations that are safe enough, asks uncertainty-reducing questions when appropriate, and provides a proactive early warning of likely failure. Finally, we present an extension to this work which enables the robot to save time by ignoring potentially many, vanishingly-unlikely scenarios. To achieve this behavior, we frame concurrent intent recognition and adaptation as a constraint satisfaction problem, and compactly represent their associated solutions and policies using compiled structures that are updated online as new observations arise. Through the use of these compiled structures, the robot efficiently reasons about which actions to perform, as well as when to perform them - thereby ensuring decision making consistent with the team’s goals.

Author: Eduardo Salas
Publisher: Routledge
ISBN: 1136697918
Category : Psychology
Languages : en
Pages : 665

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Book Description
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.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 44

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Book Description
The rapid growth in research and development of agent-based software systems has led to concerns about how human users will control the activities of teams of agents that must actively collaborate. Practical multi-agent systems will often be comprised of small teams of heterogeneous agents, under direct supervision by users acting as "team leaders". This research focused on a number of areas critical to tasking and managing teams of humans and agents, including techniques for agentizing' legacy systems, Human-Computer Interaction techniques for interactively defining tasks and roles and communications between agents, mechanisms for interactively forming and controlling teams of agents as well as summarizing and visualizing agent task status, methods for translating information across different ontologies, and mechanisms for monitoring and controlling agent communications based on semantic content. A key contribution of this work has been the development of an approach to dynamic information sharing among agents on teams, alleviating human managers from the need to coordinate information awareness. The work was demonstrated in a number of large-scale demonstrations including the Coalition Agents experiment (CoAX) and the Mixed-Initiative Agent Team Administration (MIATA) demonstration.

Author: Arup Kumar Sadhu
Publisher: John Wiley & Sons
ISBN: 1119699029
Category : Computers
Languages : en
Pages : 320

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Book Description
Discover the latest developments in multi-robot coordination techniques with this insightful and original resource Multi-Agent Coordination: A Reinforcement Learning Approach delivers a comprehensive, insightful, and unique treatment of the development of multi-robot coordination algorithms with minimal computational burden and reduced storage requirements when compared to traditional algorithms. The accomplished academics, engineers, and authors provide readers with both a high-level introduction to, and overview of, multi-robot coordination, and in-depth analyses of learning-based planning algorithms. You'll learn about how to accelerate the exploration of the team-goal and alternative approaches to speeding up the convergence of TMAQL by identifying the preferred joint action for the team. The authors also propose novel approaches to consensus Q-learning that address the equilibrium selection problem and a new way of evaluating the threshold value for uniting empires without imposing any significant computation overhead. Finally, the book concludes with an examination of the likely direction of future research in this rapidly developing field. Readers will discover cutting-edge techniques for multi-agent coordination, including: An introduction to multi-agent coordination by reinforcement learning and evolutionary algorithms, including topics like the Nash equilibrium and correlated equilibrium Improving convergence speed of multi-agent Q-learning for cooperative task planning Consensus Q-learning for multi-agent cooperative planning The efficient computing of correlated equilibrium for cooperative q-learning based multi-agent planning A modified imperialist competitive algorithm for multi-agent stick-carrying applications Perfect for academics, engineers, and professionals who regularly work with multi-agent learning algorithms, Multi-Agent Coordination: A Reinforcement Learning Approach also belongs on the bookshelves of anyone with an advanced interest in machine learning and artificial intelligence as it applies to the field of cooperative or competitive robotics.

Author: Henderson-Sellers, Brian
Publisher: IGI Global
ISBN: 1591405874
Category : Education
Languages : en
Pages : 428

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Book Description
"The book presents, analyzes and compares the most significant methodological approaches currently available for the creation of agent-oriented software systems"--Provided by publisher.