Mobile recommender systems have the potential to substantially enrich tourist experiences. As their handling marks a big challenge for ordinary users, its acceptance can only be e...
Marko Modsching, Ronny Kramer, Klaus ten Hagen, Ul...
Verbal and non-verbal interaction capabilities for robots are often studied isolated from each other in current research trend because they largely contribute to different aspects...
Although there are high expectations for collaborative discussion and on-line learning, existing systems for on-line discussion and chat facilities are not fully effective in prom...
We address the problem of users creating visualizations to debug and understand multi-agent systems. The key challenges are that (1) needs arise dynamically, i.e., it is difficult...
Jing Jin, Rajiv T. Maheswaran, Romeo Sanchez, Pedr...
We regularly operate under the notion that one agent assists another when the first does something for the second. However, the story behind this is much more complicated. In thi...
Effective human-robot cooperation requires robotic devices that understand human goals and intentions. We frame the problem of intent recognition as one of tracking and predicting...
As computer systems continue to grow in power and access more networked content and services, we believe there will be an increasing need to provide more user-centric systems that...
Assisting users with To Do lists presents new challenges for intelligent user interfaces. This paper presents our approach and an implemented system, BEAM, to process To Do list e...
We build the generic methodology based on machine learning and reasoning to detect the patterns of interaction between conflicting agents, including humans and their assistants. L...
In this paper we describe Towel, a task management application that couples a user’s to-do list with a software personal assistant. This to-do list provides a unified environmen...