FOMLAS 2018
Date: Apr 20, 2018 4:00 pm – Apr 21, 2018 3:45 pm
Location: Thessaloniki, Greece
First Workshop on Formal Methods for ML-Enabled Autonomous Systems (FOMLAS 2018)
AIM:
After the well-known DARPA Urban challenge, there have been significant improvements towards autonomous driving. In the past few years, the major theme when building self-driving cars has shifted to deep learning and probabilistic techniques. When these new algorithms act as key components in autonomous driving, they create substantial technological challenges in terms of explainability (e.g., can I explain what is happening inside the machine-learning algorithm?), predictability and correctness (e.g., can I predict what will happen next in the algorithm, or how good can the machine learning component generalize?), and accountability (e.g., when an accident occurs, can one find the root cause, or who is the one to blame?).
This goal of this workshop is to facilitate discussion regarding how formal methods can be used to increase predictability, explainability, and accountability of ML-enabled autonomous systems. The workshop welcomes results from concept formulation (by connecting these concepts with existing research topics in logic and games), as well as algorithms, tools or concrete case studies.
IMPORTANT DATES (AoE):
Submission date: 10 February 2018
Notification date: 3 March 2018
Final papers due: 24 March 2018
EPTCS proceedings due: 1 May 2018
ORGANIZATION
Workshop Co-chairs
- Chih-Hong Cheng, fortiss - Landesforschungsinstitut des Freistaats Bayern
- Indranil Saha, IIT Kanpur
Advisory board
- Harald Ruess, fortiss, Germany
- John Rushby, SRI International, USA
Program Committee (till 2017.09.11)
- Yu-Fang Chen, Academia Sinica, Taiwan
- Rudiger Ehlers, Univ. Bremen, Germany
- Jyotirmoy Deshmukh, USC, USA
- Xiaowei Huang, Univ. Liverpool, UK
- Rupak Majumdar, MPI-SWS, Germany
- Ivan Papusha, UT Austin, USA
- Harald Ruess, fortiss, Germany
- John Rushby, SRI International, USA
- Starvos Tripakis, Aalto University, Finland
Local arrangement
- Georg Nuhrenberg, fortiss - Landesforschungsinstitut des Freistaats Bayern
CONTACT:
Chih-Hong Cheng <cheng@fortiss.org>
Indranil Saha <isaha@cse.iitk.ac.in>
Submitted by Emily Wehby
on
First Workshop on Formal Methods for ML-Enabled Autonomous Systems (FOMLAS 2018)
AIM:
After the well-known DARPA Urban challenge, there have been significant improvements towards autonomous driving. In the past few years, the major theme when building self-driving cars has shifted to deep learning and probabilistic techniques. When these new algorithms act as key components in autonomous driving, they create substantial technological challenges in terms of explainability (e.g., can I explain what is happening inside the machine-learning algorithm?), predictability and correctness (e.g., can I predict what will happen next in the algorithm, or how good can the machine learning component generalize?), and accountability (e.g., when an accident occurs, can one find the root cause, or who is the one to blame?).
This goal of this workshop is to facilitate discussion regarding how formal methods can be used to increase predictability, explainability, and accountability of ML-enabled autonomous systems. The workshop welcomes results from concept formulation (by connecting these concepts with existing research topics in logic and games), as well as algorithms, tools or concrete case studies.
IMPORTANT DATES (AoE):
Submission date: 10 February 2018
Notification date: 3 March 2018
Final papers due: 24 March 2018
EPTCS proceedings due: 1 May 2018
ORGANIZATION
Workshop Co-chairs
- Chih-Hong Cheng, fortiss - Landesforschungsinstitut des Freistaats Bayern
- Indranil Saha, IIT Kanpur
Advisory board
- Harald Ruess, fortiss, Germany
- John Rushby, SRI International, USA
Program Committee (till 2017.09.11)
- Yu-Fang Chen, Academia Sinica, Taiwan
- Rudiger Ehlers, Univ. Bremen, Germany
- Jyotirmoy Deshmukh, USC, USA
- Xiaowei Huang, Univ. Liverpool, UK
- Rupak Majumdar, MPI-SWS, Germany
- Ivan Papusha, UT Austin, USA
- Harald Ruess, fortiss, Germany
- John Rushby, SRI International, USA
- Starvos Tripakis, Aalto University, Finland
Local arrangement
- Georg Nuhrenberg, fortiss - Landesforschungsinstitut des Freistaats Bayern
CONTACT:
Chih-Hong Cheng <cheng@fortiss.org>
Indranil Saha <isaha@cse.iitk.ac.in>