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» Real-World Limits to Algorithmic Intelligence
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AAAI
2008
15 years 6 months ago
Towards Faster Planning with Continuous Resources in Stochastic Domains
Agents often have to construct plans that obey resource limits for continuous resources whose consumption can only be characterized by probability distributions. While Markov Deci...
Janusz Marecki, Milind Tambe
AIPS
2008
15 years 6 months ago
Bounded-Parameter Partially Observable Markov Decision Processes
The POMDP is considered as a powerful model for planning under uncertainty. However, it is usually impractical to employ a POMDP with exact parameters to model precisely the real-...
Yaodong Ni, Zhi-Qiang Liu
AAAI
2010
15 years 5 months ago
Efficient Spectral Feature Selection with Minimum Redundancy
Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...
Zheng Zhao, Lei Wang, Huan Liu
AAAI
2011
14 years 4 months ago
End-User Feature Labeling via Locally Weighted Logistic Regression
Applications that adapt to a particular end user often make inaccurate predictions during the early stages when training data is limited. Although an end user can improve the lear...
Weng-Keen Wong, Ian Oberst, Shubhomoy Das, Travis ...
ATAL
2009
Springer
15 years 11 months ago
Constraint-based dynamic programming for decentralized POMDPs with structured interactions
Decentralized partially observable MDPs (DEC-POMDPs) provide a rich framework for modeling decision making by a team of agents. Despite rapid progress in this area, the limited sc...
Akshat Kumar, Shlomo Zilberstein