Eric Horvitz to give the keynote at HAIDM2016

Eric-horvitz-microsoft-portraitEric Horvitz is the Director of the Microsoft Research lab at Redmond. Pursuing research on principles of machine intelligence and on leveraging the complementarities of human and machine reasoning. Passionate about harnessing the latest computing advances to provide valuable services.

Horvitz received his PhD in 1990 and his MD degree at Stanford University.[2] His doctoral dissertation, Computation and action under bounded resources, and follow-on research introduced models of bounded rationality founded in probability and decision theory. He did his doctoral work under advisors Ronald A. Howard, George B. Dantzig, Edward H. Shortliffe, and Patrick Suppes.

He is currently Technical Fellow at Microsoft, where he serves as director of Microsoft Research‘s main Redmond lab. He has been elected Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), the National Academy of Engineering (NAE), the American Academy of Arts and Sciences, and of the American Association for the Advancement of Science (AAAS). He was elected to the ACM CHI Academy in 2013 and ACM Fellow 2014 For contributions to artificial intelligence, and human-computer interaction.[3]

He was awarded the Feigenbaum Prize, a biennial award for sustained and high-impact contributions to the field of artificial intelligence through the development of computational models of perception, reflection and action, and their application in time-critical decision making, and intelligent information, traffic, and healthcare systems.

Note: Excepts from Eric’s homepage and Wikipedia entry.

HAIDM 2016 to be held in conjunction with IJCAI 2016

Call for Papers

 Fifth International Workshop on Human-Agent Interaction Design and Models (HAIDM 2016), co-located with IJCAI 2016

Monday, July 11, 2016

We are vey pleased to host Eric Horvitz (MSR) as the invited speaker for HAIDM 2016  

Workshop Goals

As the boundaries of autonomous agents and multi-agent systems continue to expand, there is an increasing need for agents to interact with humans.  In fact, the field of multi-agent systems has matured from conceptual models to applications within the real-world (e.g., energy and sustainability, disaster management, or health care).  One significant challenge that arises when transitioning these conceptual models to applications is addressing the inevitable human interaction.  To this end, this workshop examines major challenges at the intersection of human-agent systems. In particular, we focus on the challenges of designing and modelling human-agent interaction. While the former takes a human-centric view of human-agent systems and focuses on the design of human-agent coordination mechanisms, trust issues in human-agent interaction, interaction techniques, and human activity recognition, the latter is concerned with finding better models of human behaviour in a variety of settings so that autonomous and multi-agent systems can appropriately interact with human agents (e.g., agent-human negotiation strategies or health care agents encouraging physical therapy for a variety of recovering patients).

Topics Covered

  • Models of Human Behaviour: this may include studies drawing the behavioural game theory literature or solutions that attempt to model human response in collaborative and competitive relationships with agents/robots.
  • Systems of Humans and Agents (incl. Robots): systems that interleave humans and agents in flexible relationships and teams. This may include interactions with autonomous vehicles, robots, and software agents in both cooperative and strategic settings.
  • Crowdsourcing: models, algorithms and techniques for effective problem solving in crowdsourcing including social incentives, micro-payments for micro-tasks, learning about workers and tasks, task allocation, collaborative problem solving and novel applications. The focus should be on combining machine and human intelligence in crowdsourcing.

We welcome  contributions that cover:

  • Theoretical results,
  • Methodological contributions,
  • Quantitative and qualitative studies of human-agent interaction (or agent-supported human activities) in the lab, online and in real-world settings

The HAIDM workshop, now in its fifth  year, brings together a vibrant community of researchers interested in modeling human behavior as well as improving agent designs for interacting with people. This is the first instalment of HAIDM at IJCAI.

Important Dates

Submission: 18th 30th April 2016

Acceptance Notification: 21st May 2016 (TBC)

Workshop takes place: 11th July 2016

Submission Procedure

Submissions are made using easy chair at this link:

https://easychair.org/conferences/?conf=haidm16

Submissions should conform to the LNCS Springer format,  Authors are encouraged to use the style file found here  or see http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0for more details.

Submissions may be of two types:

  • Long papers: These are full-length research papers detailing work in progress or work that could potentially be published at a major conference. These should not be more than *16* pages long in the LNCS format above.
  • Short papers: These are position papers or demo papers that describe either a project on human-agent systems, an application that has not yet been evaluated, or initial work. These should not be more than *8* pages long (excluding appendices and assuming the LNCS format above).

Programme Committee 
Ofra Amir, Harvard University
Inon Zuckerman, Ariel University
Roni Stern, Ben-Gurion University
Bo An Nanyang, Technological University
David Griol, Universidad Carlos III de Madrid, Spain
George Kampis, Eotvos University
Matteo Venanzi, University of Southampton
Deborah Richards, Macquarie University
Daniele Morandi, ThinkInside
Nader Hanna, Macquarie University
Jose M. Molina, Universidad Carlos III de Madrid
Agnes Gruenerbl, DFKI
Simone Fischer-Hübner, Karlstad University
Daniela Dybalova, The University of Nottingham
Vincenzo Maltese, University of Trento
Amos Azaria, Carnegie Mellon University
Elizabeth Sklar, King’s College London
Arielle Richardson, Jerusalem College of Technology
Michael Rovatsos, School of Informatics, The University of Edinburgh
Ladislau Boloni, University of Central Florida

Organising Committee

Sarvapali D. Ramchurn, University of Southampton, UK
Avi Rosenfeld, Jerusalem College of Technology, Israel
Kobi Gal, Ben Gurion University, Israel
Ece Kamar, Microsoft Research (Redmond), USA

invited talk – Jon Gratch

The promise and peril of anthropomorphizing agents

Advances in autonomy raise the potential for rich partnerships between humans and machines. Recent scholarship has explored the potential of incorporating human-like traits into robot and computer teammates as a means to enhance team effectiveness. However, whereas a growing body of research illustrates that machines can be made more human-like, less research has considered how this benefits or harms human-machine team performance. Indeed, I will illustrates several examples where human-like qualities actually undermine team performance. More fundamentally, attempts to merely replicate human characteristics overlook an opportunity to improve on human-human interaction: perhaps machines can be designed to interact in different but complementary ways that draw on those social mechanisms that benefit team outcomes while avoiding those that detract from this goal. In this talk, I will illustrate several projects examining the difference between behavior towards human-like and non-human machines and discuss a preliminary theoretical framework for guiding the design of effective, rather than anthropomorphic, human-agent interactions.

Jonathan Gratch (http://www.ict.usc.edu/~gratch) is Director for Virtual Human Research at the University of Southern California’s (USC) Institute for Creative Technologies, a Research Full Professor of Computer Science and Psychology at USC and director of USC’s Computational Emotion Group. He completed his Ph.D. in Computer Science at the University of Illinois in Urban-Champaign in 1995.  Dr. Gratch’s research focuses on computational models of human cognitive and social processes, especially emotion, and explores these models’ role in shaping human-computer interactions in virtual environments. He studies the relationship between cognition and emotion, the cognitive processes underlying emotional responses, and the influence of emotion on decision making and physical behavior. He is the founding and current Editor-in-Chief of IEEE’s Transactions on Affective Computing (3.5 impact factor in 2013), Associate Editor of Emotion Review and the Journal of Autonomous Agents and Multiagent Systems, and former President of the Association for the Advancement of Affective Computing (AAAC). He is a AAAI Fellow, a SIGART Autonomous Agent’s Award recipient, a Senior Member of IEEE, and member of the International Society for Research on Emotion (ISRE).  Dr. Gratch is the author of over 200 technical articles.

IMG_1063

HAIDM 2015 CFP

Call for Papers

 Fourth International Workshop on Human-Agent Interaction Design and Models (HAIDM 2015)

co-located with AAMAS 2015 (4th of May).

HAIDM 15 is co-organized with the SMARTSOCIETY project funded by the EC under FP7 Future Emerging Technologies programme.

Workshop Goals

As the boundaries of autonomous agents and multi-agent systems continue to expand, there is an increasing need for agents to interact with humans.  In fact, the field of multi-agent systems has matured from conceptual models to applications within the real-world (e.g., energy and sustainability, disaster management, or health care).  One significant challenge that arises when transitioning these conceptual models to applications is addressing the inevitable human interaction.  To this end, this workshop examines major challenges at the intersection of human-agent systems. In particular, we focus on the challenges of designing and modelling human-agent interaction. While the former takes a human-centric view of human-agent systems and focuses on the design of human-agent coordination mechanisms, trust issues in human-agent interaction, interaction techniques, and human activity recognition, the latter is concerned with finding better models of human behaviour in a variety of settings so that autonomous and multi-agent systems can appropriately interact with human agents (e.g., agent-human negotiation strategies or health care agents encouraging physical therapy for a variety of recovering patients).

Topics Covered

– Flexible autonomy – how should the delegation of tasks to agents be performed such that the right degree of autonomy be given to individual agents or teams of such agents to optimise the performance of tasks by a human controller or to support  activities of teams of humans interacting with (teams of) agents.

– Trust between humans and agents – when humans delegate tasks to agents or vice-versa, they need to be able to capture the uncertainty in the other party being able to correctly complete tasks or activities. Such uncertainty may be modelled using  past interactions (trust) or information gathered from other agents (reputation). Developing effective trust and reputation models and mechanisms for human-agent interaction is therefore key to establishing long term relationships between humans and agents.

– Presentation and interaction techniques – to allow users to understand and modify the actions of large collections of agents as they reason and act on behalf of users.

–  Smart society applications including energy systems, ridesharing, healthcare augmentation, disaster response where agents and humans need to cooperate/coordinate to achieve joint objectives to solve problems involving issues of scale, spatial distribution, and heterogeneity in the capabilities available given to the actors in the system.

– Coalition formation and optimisation models involving models of agents and humans.

– Human-Robot Interaction: the design of embodied agents for believability and trust as well as methods for human-robot coordination.

– Crowdsourcing: models, algorithms and techniques for effective problem solving in crowdsourcing including social incentives, micro-payments for micro-tasks, learning about workers and tasks, task allocation, collaborative problem solving and novel applications. The focus should be on combining machine and human intelligence in crowdsourcing.

– Citizen science: the use of agent-based techniques to facilitate citizen scientists to contribute to the solution of scientific problems in platforms such as Zooniverse, Foldit and eBird, including studies of motivation, incentives, quality control and task allocation.

– Use of agent-based coordination algorithms to coordinate humans.

– Enhanced models of human behaviour and theory of human behaviour

– Comparison of approaches in applying models of human behaviour (e.g., bounded rational or psychological models)

– Applications of human behaviour models

– Cooperative and competitive agent-human systems

– Behavioural game theory

– Techniques for learning human behaviour (e.g., machine learning, crowdsourcing, and human computation)

– Benchmarks and evaluation methodologies for evaluating agent-human interactions

– Quantitative and qualitative studies of human-agent interaction (or agent-supported human activities) in the lab, online and in real-world settings

Important Dates

11th February: 23rd February: Submission deadline

10th March: Notifications

19th March: Deadline for Camera-Ready copies

Submission Procedure

Submissions should conform to the LNCS Springer format,  Authors are encouraged to use the style file found here  or see http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0for more details.

Submissions may be of two types:

  • Long papers: These are full-length research papers detailing work in progress or work that could potentially be published at a major conference. These should not be more than *16* pages long in the LNCS format above.
  • Short papers: These are position papers or demo papers that describe either a project on human-agent systems, an application that has not yet been evaluated, or initial work. These should not be more than *8* pages long (excluding appendices and assuming the LNCS format above).

Authors can submit their papers through the HAIDM 2015 Easychair submission site https://easychair.org/conferences/?conf=haidm15

Programme Committee

Matteo Venanzi University of Southampton
Bo An Nanyang Technological University
Rui Prada INESC-ID and Instituto Superior Técnico, Universidade de Lisboa
David Griol Universidad Carlos III de Madrid, Spain
Vincenzo Maltese University of Trento
Hirotaka Osawa University of Tsukuba
Ariella Richardson Jerusalem College of Technology
Frank Dignum Utrecht University
Michael Rovatsos School of Informatics, The University of Edinburgh
Subramanian Ramamoorthy University of Edinburgh
Heather S. Packer University of Southampton
Jose M. Molina Universidad Carlos III de Madrid
Deborah Richards Macquarie University
Thanh Nguyen University of Southern California
Arlette Van Wissen Utrecht University
George Kampis Eotvos University
David Robertson University of Edinburgh
Robert Loftin North Carolina State University
Nader Hanna Macquarie University
Inon Zuckerman Ariel University Center
Virginia Dignum TU Delft
Amos Azaria Carnegie Mellon University
Ognjen Scekic Vienna University of Technology
Joana Campos Technical University of Lisbon and INESC-ID
Ladislau Boloni University of Central Florida
Daniele Miorandi
Matthew E. Taylor Washington State University
Çetin Meriçli Carnegie Mellon University
Andreadis Pavlos
Daniela Dybalova The University of Nottingham
Simone Fischer-Hübner Karlstad University
Ana Paiva INESC
Claudia Goldman General Motors
Elizabeth Sklar University of Liverpool

Organising Committee

Sarvapali D. Ramchurn, University of Southampton, UK
Avi Rosenfeld, Jerusalem College of Technology, Israel
Kobi Gal, Ben Gurion University, Israel
Ece Kamar, Microsoft Research (Redmond), USA
Joel Fischer, University of Nottingham, UK

SPONSORS

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