Message posted on 07/08/2020

CfP: Formal Methods for Autonomous Systems (FMAS2020)

Second Workshop on Formal Methods for Autonomous Systems (FMAS 2020)
This one day workshop will bring together researchers working on a range of techniques for formal verification of autonomous systems, to present recent work in the area, discuss key difficulties, and stimulate collaboration between the robotics and formal methods communities. This workshop will include invited speakers, contributed papers, and experience reports.

FMAS202 will be held online, due to the ongoing disruption caused by COVID-19. Since many of the conferences that we were looking to for hosting the workshop are not accepting satellite events, FMAS2020 will run on its own.
More details can be found on our website: https://autonomy-and-verification-uol.github.io/events/fmas2020
Important Dates
Submission: 11th of September 2020

Notification: 23rd of October 2020

Final Version due: 6th of November 2020

Workshop (online): 7th of December 2020

Scope
Autonomous -- and Robotic -- Systems present unique challenges for formal methods. They are embodied entities that can interact with the real world and make autonomous decisions. Amongst others, they can be viewed as safety-critical, cyber-physical, hybrid, and real-time systems. Key issues for formal methods applied to autonomous systems include capturing how the system will deal with a dynamic external environment and verification of the system's decision making capabilities -- including planning, safety, ethical, and reconfiguration choices. Some autonomous systems require certification before deployment, others require public trust for wide adoption; both of these scenarios are being tackled by formal methods.

The goals of this workshop are to bring together leading researchers in this area to present recent and ongoing work, including experience reports and case studies as well as identify future directions for this emerging application of formal methods. This workshop is concerned with the use of formal methods to specify, model, or verify autonomous or robotic systems, in whole or in part. Submissions may focus on case studies that identify the challenges for formal methods in this area, or experience reports that provide guidelines for tackling these challenges.
We are especially interested in work using integrated formal methods, discussing the future directions of the field, using Runtime Verification or other approaches to deal with the reality gap, the cross over of safety and security, and verification of systems against safety assurance arguments or standards documents.
Submission Information
Topics of interest include (but are not limited to):

Experience reports/case studies on applying formal methods to autonomous and/or robotic systems,
Novel formal methods that can be applied to autonomous and/or robotic systems,

The modification of existing formal methods to suit autonomous and/or robotic systems, and

Future directions for formal methods for autonomous and/or robotic systems.

There are two categories of submission:

Short papers -- 6 pages, suitable for overviews of an approach or work-in-progress. Work from PhD students is particularly welcome;
Long papers -- 15 pages, suitable for descriptions of completed studies, new approaches, or new directions.

Submission will be via easychair (https://easychair.org/conferences/?conf=fmas2020) and submissions must be prepared using the EPTCS LaTeX style (http://style.eptcs.org/). Accepted papers will be published via EPTCS (http://www.eptcs.org/).

Each submission will receive at least three, single-blind reviews. If a paper is accepted, at least one of the authors must attend the workshop to present their work.
Venue
This year, FMAS will be held online via a video conference system. We will circulate details closer to the event, when the number of attendees is clearer.

Chairs
Marie Farrell marie.farrell@manchester.ac.uk (mailto:marie.farrell@manchester.ac.uk), University of Manchester, UK

Michael Fisher, University of Manchester, UK

Matt Luckcuck matthew.luckcuck@manchester.ac.uk (mailto:matthew.luckcuck@manchester.ac.uk), University of Manchester, UK
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