AASS Seminar - Integrating Reasoning and Learning over Streams for Safe Autonomous Systems

The research centre AASS arranges a seminar with Fredrik Heintz, Linkoping University, Sweden.

Abstract

We live in a streaming world. New information is continually being produced by sensors and humans. A stream is such a sequence of incrementally available information. Streaming information is always dynamic and temporal, and usually also spatial in nature. Reasoning over these streams is necessary to draw conclusions and make decisions in real-time. Since streams are conceptually infinite, this reasoning has to be done incrementally as new information becomes available. The incremental reasoning over streams is called stream reasoning. Stream reasoning addresses at least three of four V's in BigData: Velocity, Variety and Veracity.

This talk gives an overview of the state-of-the-art in efficient and scalable logic-based approaches to spatio-temporal stream reasoning with incomplete information suitable for execution monitoring of autonomous systems. It also outlines current research on integrating learning into the stream reasoning framework to monitor not only the current execution but also the predicted future execution of the system.

Stream reasoning is an emerging research area with great potential and strategic relevance for autonomous systems, the Internet of Things and real-time data analytics. An important application is online verification of autonomous systems. These systems are too large and too complex to be modeled in detail. Therefore model checking is not a viable option. Instead, stream reasoning can be used to provide run-time verification by continually monitoring the system execution with formal guarantees to make sure that it behaves as expected.

Speakers' Bio

Dr. Fredrik Heintz is an Associate Professor of Computer Science at Linkoping University, Sweden. He leads the Stream Reasoning group within the Division of Artificial Intelligence and Integrated Systems (AIICS).  His research focus is artificial intelligence and autonomous systems. He has for example contributed to the areas of incremental spatio-temporal reasoning over streaming information, information integration using semantic matching, high-level situation awareness, and software architectures for collaborative unmanned aircraft systems. The main application area is collaborative unmanned aircraft systems. He is also the Director of the Wallenberg Autonomous Systems and Software Program (WASP) Graduate School with 105 PhD students, the President of the Swedish AI Society and the Local Arrangements Chair for IJCAI-ECAI-18 in Stockholm.