Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Abstract. The emergence of data-intensive applications in mobile environments has resulted in portable electronic systems with increasingly large dynamic memories. The typical oper...
Cyber-physical systems increasingly rely on dynamically adaptive programs to respond to changes in their physical environment; examples include ecosystem monitoring and disaster r...
The extension of our research on analysis of a single agent or agent communities combining advanced methods of visualization with traditional AI techniques is presented in this pa...