Activity recognition based on data from mobile wearable devices is becoming an important application area for machine learning. We propose a novel approach based on a combination ...
We discuss challenges and opportunities for developing generalized task markets where human and machine intelligence are enlisted to solve problems, based on a consideration of th...
We consider the task of assigning experts from a portfolio of specialists in order to solve a set of tasks. We apply a Bayesian model which combines collaborative filtering with a...
David H. Stern, Horst Samulowitz, Ralf Herbrich, T...
We report a new error-aware monocular visual odometry method that only uses vertical lines, such as vertical edges of buildings and poles in urban areas as landmarks. Since vertic...
Intentions have been widely studied in AI, both in the context of decision-making within individual agents and in multiagent systems. Work on intentions in multi-agent systems has...
The behavior of a complex system often depends on parameters whose values are unknown in advance. To operate effectively, an autonomous agent must actively gather information on t...
Li Ling Ko, David Hsu, Wee Sun Lee, Sylvie C. W. O...
Computer agents are increasingly deployed in settings in which they make decisions with people, such as electronic commerce, collaborative interfaces, and cognitive assistants. Ho...
Raz Lin, Sarit Kraus, Yinon Oshrat, Ya'akov (Kobi)...
Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...
Thomas J. Walsh, Sergiu Goschin, Michael L. Littma...
Modern complex games and simulations pose many challenges for an intelligent agent, including partial observability, continuous time and effects, hostile opponents, and exogenous ...
Research on information extraction (IE) seeks to distill relational tuples from natural language text, such as the contents of the WWW. Most IE work has focussed on identifying st...