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