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AGENTS
1998
Springer
14 years 3 months ago
Learning Situation-Dependent Costs: Improving Planning from Probabilistic Robot Execution
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
Karen Zita Haigh, Manuela M. Veloso
ATAL
2006
Springer
14 years 2 months ago
RPD-enabled agents teaming with humans for multi-context decision making
Team decision making under stress involving multiple contexts is an extremely challenging issue faced by various real world application domains. This research is targeted at coupl...
Xiaocong Fan, Bingjun Sun, Shuang Sun, Michael D. ...
AAAI
2010
14 years 10 days ago
Efficient Lifting for Online Probabilistic Inference
Lifting can greatly reduce the cost of inference on firstorder probabilistic graphical models, but constructing the lifted network can itself be quite costly. In online applicatio...
Aniruddh Nath, Pedro Domingos
SDM
2010
SIAM
226views Data Mining» more  SDM 2010»
14 years 10 days ago
Two-View Transductive Support Vector Machines
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam...
Guangxia Li, Steven C. H. Hoi, Kuiyu Chang
IJCAI
2007
14 years 9 days ago
Color Learning on a Mobile Robot: Towards Full Autonomy under Changing Illumination
A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. It is commonly asserted that in order to ...
Mohan Sridharan, Peter Stone