FOMC Proceedings now appear online at:

FOMC Program:

8:30: Invited Talk
Dealing with Uncertainty in Wireless Communication
Fabian Kuhn

Distributed Queuing in Dynamic Networks,
Gokarna Sharma and Costas Busch

Relative Throughput – Measuring the Impact of Adversarial Errors on Packet Scheduling Strategies,
Antonio Fernandez Anta, Chryssis Georgiou, Dariusz R. Kowalski, Joerg Widmer and Elli Zavou

10:20: coffee break

10:35: Invited Talk
Reusable Teamwork for Multi-Robot Teams
Gal Kaminka

Message and time efficient multi-broadcast schemes,
Liron Levin, Dariusz R. Kowalski and Michael Segal

Robust Leader Election in a Fast-Changing World,
John Augustine, Tejas Kulkarni, Paresh Nakhe and Peter Robinson

Jamming-Resistant Learning in Wireless Networks,
Johannes Dams, Martin Hoefer and Thomas Kesselheim

12:50:short break

FOMC Business Meeting


Invited Talks:

Gal Kaminka, Bar-Ilan University

Title:Reusable Teamwork for Multi-Robot Teams


For many years, multi-robot researchers have focused on specific
application-inspired basic tasks (e.g., coverage, moving in
formation, foraging, patrolling) as a way of studying cooperation
between robots. But users want to see increasingly complex missions
being tackled, which challenge this methodology: first, some missions
cannot be easily decomposed into the familiar basic tasks,
making previous knowledge non-reusable; second, the target operating
environments challenge the typically sterile settings assumed in
many previous works (such challenges include adversaries, multiple
concurrent goals, human operators and users, and more).

In this talk, I will argue that the reusable components in complex
missions are often found not in the tasks, but in the interactions between
robots, i.e., that while taskwork varies significantly, teamwork is
largely generic. And while many multi-robot researchers have begun exploring
generic task-allocation methods, I will report on my group’s work over
the last decade, identifying and developing other general mechanisms for teamwork,
and integrating them at the architecture level to facilitate development

of robust teams at reduced programming effort. I will sample some of
our results in developing robots for missions ranging from robust formation
maintenance, through patrolling, to soccer and urban search-and-rescue.


Gal A. Kaminka is an associate professor at the computer science
department and the brain sciences research center, at Bar Ilan
University (Israel), where he chairs the Bar Ilan University
Robotics Consortium. His research expertise includes multi-agent and
multi-robot systems, teamwork and coordination, behavior and plan
recognition, and modeling social behavior. He received his PhD
from the University of Southern California (2000), spent time
as a post-doctorate fellow at Carnegie Mellon University (until 2002),
and a year as a Radcliffe Fellow at Harvard University’s Radcliffe
Institute for Advanced Study (2012).  Prof. Kaminka was awarded an
IBM faculty award and top places at international robotics competitions.
He served as the program chair of the 2008 Israeli Conference on
Robotics, and the program co-chair of the 2010 Int’l Joint Conference
on Autonomous Agents and Multi-Agent Systems (AAMAS). He has served
on the international executive bodies of IFAAMAS (International Foundation
of Autonomous Agents and Multi-Agent Systems) and AAAI (Association for
Advancement of Artificial Intelligence).

Fabian Kuhn, University of Freiburg

Title: Dealing with Uncertainty in Wireless Communication


Over the last 25 years, a variety of abstract models to deal with the characteristic properties of wireless communication have been proposed and many algorithms for wireless networks have been developed. The models range from simple graph-based characterizations of interference to more accurate so-called signal-to-noise-and-interference (SINR) models. As different as the considered models may be, most of them have one thing in common. Whether a node can successfully receive (and

decode) a message is determined using some fixed, deterministic rule that depends on the structure of the network and some additional model parameters. Often correctness and performance guarantees of algorithms critically depend on such rigid rules and sometimes even on the fact that each node exactly knows certain model parameters or some other information about the network. In my talk, I will argue that such assumptions can be problematic and I will discuss some existing results and future directions to deal with inherent uncertainties in systems based on wireless communication.