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CI
2005
106views more  CI 2005»
15 years 3 months ago
Incremental Learning of Procedural Planning Knowledge in Challenging Environments
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
Douglas J. Pearson, John E. Laird
117
Voted
ROBOCUP
2005
Springer
151views Robotics» more  ROBOCUP 2005»
15 years 9 months ago
Sequential Pattern Mining for Situation and Behavior Prediction in Simulated Robotic Soccer
Agents in dynamic environments have to deal with world rep- To appear in: RoboCup 2005: Robot Soccer World Cup IX, c Springer-Verlag, 2006 resentations that change over time. In or...
Andreas D. Lattner, Andrea Miene, Ubbo Visser, Ott...
156
Voted
CSREAPSC
2006
15 years 5 months ago
Modelling Application Handovers For Thin-Client Mobility
Mobile users need lightweight devices with low energy consumption. When applications are executed on remote servers instead of locally on the end-user's device, the weight of...
Pieter Simoens, Lien Deboosere, Davy De Winter, Fi...
JCM
2008
77views more  JCM 2008»
15 years 3 months ago
In-Field Attack Proof of Injected False Data in Sensor Networks
In a large-scale sensor network individual sensors can be compromised to inject bogus sensing reports. While SEF can filter out the outfield false reports, it is incapable of detec...
Zheng Wang, Xiaodong Lee, Xinchang Zhang, Baoping ...
145
Voted
ASPLOS
2006
ACM
15 years 9 months ago
Temporal search: detecting hidden malware timebombs with virtual machines
Worms, viruses, and other malware can be ticking bombs counting down to a specific time, when they might, for example, delete files or download new instructions from a public we...
Jedidiah R. Crandall, Gary Wassermann, Daniela A. ...