Sequential Plan Recognition

Abstract: Plan recognition algorithms need to maintain all candidate hypotheses which are consistent with the observations, even though there is only a single hypothesis that is the correct one. Unfortunately, the number of possible hypotheses can be exponentially large in Continue reading

SLIM: Semi-Lazy Inference Mechanism for Plan Recognition

Abstract: Plan Recognition algorithms require to recognize a complete hierarchy explaining the agent’s actions and goals. While the output of such algorithms is informative to the recognizer, the cost of its calculation is high in run-time, space, and completeness. Moreover, Continue reading

Intervention Strategies for Increasing Engagement in Volunteer-Based Crowdsourcing

Abstract: Volunteer-based crowdsourcing depend critically on maintaining the engagement of participants. We explore a methodology for extending engagement in citizen science by combining machine learning with intervention design. We first present a platform for using real-time predictions about forthcoming disengagement Continue reading

Which Is the Fairest (Rent Division) of Them All?

Abstract: What is a fair way to assign rooms to several housemates, and divide the rent between them? This is not just a theoretical question: many people have used the Spliddit website to obtain envy-free solutions to rent division instances. Continue reading

Semantics and Provenance for Accountable Smart City Applications, The Role of Semantics in Smart Cities

Abstract: The recent media focus on Smart City services, particularly ride sharing, that provide ordinary users with the ability to advertise their resources has highlighted society’s need for transparent and accountable systems. Current systems offer little transparency behind their processes Continue reading