Representing navigational affordance based on high-level knowledge of scenes

Automatic High Level Avatar Guidance Based on Affordance of Movement

As virtual cities become ever more common and more extensive, the need to populate them with virtual pedestrians grows. One of the problems to be resolved for the virtual population is the behaviour simulation. Currently specifying the behaviour requires a lot of laborious work. In this paper we propose a method for automatically deriving the high level behaviour of the avatars. We introduce to...

Representing and learning affordance-based behaviors

Scene Affordance: Inferring Actions from Household Scenes

In order to be helpful some day, robots do not only need to perceive their environment accurately but also have to be capable of carrying out appropriate tasks automatically. In a household setting, it is desirable to have a robot that does not require explicit instructions but rather identifies relevant tasks automatically. We suggest to approach this challange by collecting a large dataset wh...

Representing Guidelines Using Domain-level Knowledge Components

Aziz A. Boxwala, M.B.B.S., Ph.D., Purvi Mehta, M.B.B.S., Mor Peleg, Ph.D., Ronilda Lacson, M.D. , Nachman Ash, M.D. , Jonathan Bury, M.B.Ch.B., Edward H. Shortliffe, M.D., Ph.D., Robert A. Greenes, M.D., Ph.D. 1 Decision Systems Group, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; 2 Stanford Medical Informatics, Stanford University, Stanford, CA; 3 Department of Medical Info...

Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data

Observations of individual organisms (data) can be combined with expert ecological knowledge of species, especially causal knowledge, to model and extract from flower-visiting data useful information about behavioral interactions between insect and plant organisms, such as nectar foraging and pollen transfer. We describe and evaluate a method to elicit and represent such expert causal knowledge...