We present a Reverse Reinforcement Learning (Reverse RL) approach for representing retrospective knowledge .

We present a Reverse Reinforcement Learning (Reverse RL) approach for representing retrospective knowledge. General Value Functions (GVFs) have enjoyed great success in representing predictive knowledge, i.e., answering questions about possible future outcomes such as "how much fuel will be consumed in expectation if we drive from A to B?". GVFs, however, cannot answer questions like "how much fuel do we expect a car to have given it is at B at time $t$?". To answer this question, we need to know when that car had a full tank and how that car came to B. Since such questions emphasize the influence of possible past events on the present, we refer to their answers as retrospective knowledge. In this paper, we show how to represent retrospective knowledge with Reverse GVFs, which are trained via Reverse RL. We demonstrate empirically the utility of Reverse GVFs in both representation learning and anomaly detection.

Microdrones has announced that, as part of an ongoing global growth initiative, it has acquired Aircam UAV Technology, a 64 employee Chinese company that provides UAV (unmanned aerial vehicle) technologies and services. Aircam has developed a large Chinese and Southeast Asian customer base with a focus on surveying & mapping, utilities, and oil & gas industries. Aircam will be fully integrated with the Microdrones business, brand and leadership team. The Aircam brand and corporate identity will change to Microdrones, and all aspects of the business will be directed by the Microdrones global leadership team. Microdrones and Aircam have a long history of working together.