[fg-arc] [fm-announcements] CFP: Formal Verification & Modeling in Human-Machine Systems

[Rungta, Neha S. (ARC-TI)[Stinger Ghaffarian Technologies Inc. (SGT Inc.)]]

========================================================
Formal Verification & Modeling in Human-Machine Systems AAAI 2014
                    Spring Symposium (FVHMS 2014)
	http://faculty.cs.byu.edu/~mike/mikeg/WORKSHOP/
========================================================

Overview: The goal of the workshop is to bring together the fields of
formal verification, cognitive modeling, and task analysis to study
the design and verification of real human-machine systems. Recent
papers in each of these communities discuss modeling challenges and
the application of basic formal verification in human-machine
interaction; however, there is little communication between
researchers in these different areas and there are many open questions
that require cross-disciplinary collaboration. The workshop is to
bring together experts from many communities in an environment where
it is possible to explore key research areas, common solutions,
near-term research problems, and advantages in combining the best of
the different communities.

Submissions: We solicit papers describing original work either
in-progress or finished, position papers or extended abstracts
describing research or positions. Papers should follow the AAAI
formatting, with a page-limit of 6 pages. Proceedings of the symposium
will be published by AAAI as a CD, distributed at the
symposium. Selected papers will be invited to submit extended versions
of their contributions for review in a follow-on special issue of the
IEEE Transactions on Human-Machine Systems dedicated to the same
topic.
                    
Topics of Interest:

* What model classes, methodologies, and constructs are appropriate
  for modeling human and machine activities in a way that is amenable
  to formal verification? Examples include
     	   - Programming languages
           - State Machines
           - Activity models (e.g. Brahms)
           - Cognitive models (SOAR, ACT-R, DIARC, etc.)
           - Task analyses-based models (GDTA, CWA, etc.)
           - Probabilistic models
           - Behavioral game theory

* What levels of abstraction are appropriate for such modeling, and
  what information is lost in using abstraction?

* What are the contexts, if any, for which the trade offs between
  authority between humans, autonomy, and model-based reasoning can be
  specified?

* What is the impact on design for including explicit (meta-)
  reasoning models in the human-machine interaction loop?

* What types of model-checkers are appropriate, and what other lessons
  from formal verification apply to human-machine systems?

* What are the ethical considerations of using verified models to
  allocate responsibility and authority between humans and machines?

* What organizational structures are appropriate for human-machine
  collaborative work?
         - Master-slave
         - Teammates
         - Principal-agent

* How can dynamic models evolve in the presence of learning agents,
  both human and machine, and in the presence of inaccurate mental
  models.


Important Dates:                     
Oct 18, 2013: Submission deadline                    
Dec 10, 2013: Notification of acceptance/rejection                    
Jan 10, 2014: Camera-ready papers due                    
Mar 1, 2014: Registration deadline                    
March 24-26, 2014: Symposium

Organizers: 
Michael Goodrich, Brigham Young University, USA
Eric Mercer, Brigham Young University, USA
Neha Rungta, NASA Ames Research Center, USA
Ellen Bass, Drexel University, USA

Invited Speakers:
Amy Pritchett, Georgia Tech, USA
Philippe Palanque, IRIT, University Paul Sabatier, France
Christian Lebiere, CMU, USA
                
---
To opt-out from this mailing list, send an email to

fm-announcements-request at lists.nasa.gov

with the word 'unsubscribe' as subject or in the body. You can also make the request by contacting

fm-announcements-owner at lists.nasa.gov