The field of embedded reasoning is seeing a surge of interest driven by rapid advances in embedded computing power and
the desire to control increasingly complex systems safely, efficiently, and reliably. It incorporates the strengths of
AI reasoning — planning, scheduling, controlling, learning, and diagnosing — into physical systems. This advances system
capabilities in solving complex tasks, in acting on high-level goals, and in adapting to changing and uncertain states.
A number of applications are being revolutionized, from robotics to transportation systems to industrial automation.
The integrated methods by which we approach these problems are also rapidly evolving. As illustrated by recent research
programs and applications, these emerging capabilities require a tight integration of diverse techniques with a strong
multi-disciplinary understanding of their relationship. The traditional interfaces of the fields of AI reasoning, control,
and human factors are becoming blurred, with control system optimizations running on embedded processors, and artificial
intelligence controlling autonomous vehicles.
Intelligence in embedded systems faces a number of challenges to enable systems of sensors, actuators, and processors to
be adaptive, distributed, and robust. There is often a tight coupling with both the physical world and temporal requirements,
leading to challenges in real-time execution and in process and communication concurrency. Systems must be able to understand
their environment and act intelligently and often autonomously, with potentially noisy sensor inputs and imperfect models of
system behavior. They often involve the integration of capabilities such as inference, strategic and tactical planning, optimal
behavior selection, and reactive control. It is vital to consider the associated programming paradigms and approaches to
verification and fault tolerance. Systems must interact appropriately with each other and transparently with their human
operators. Embedded reasoning systems draw upon a multitude of technologies.
We invite researchers to bring perspectives from multiple disciplines including control, artificial intelligence, and human
factors research. Additionally, survey and comparison papers are welcome. The goals are to bring researchers together to
share and discuss existing techniques, present new approaches, and to learn from and celebrate recent examples of successful
experiments and applications on the frontiers of embedded reasoning. This symposium is meant to encourage direct comparisons
of theories and of implementations to unify concepts from varying perspectives, and to provide a venue for discussion on the
direction of the field.