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» The Complexity of Belief Update
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AAAI
1997
15 years 1 months ago
Incremental Methods for Computing Bounds in Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
Milos Hauskrecht
JMLR
2010
202views more  JMLR 2010»
14 years 6 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
AI
2004
Springer
14 years 11 months ago
The limitation of Bayesianism
In the current discussion about the capacity of Bayesianism in reasoning under uncertainty, there is a conceptual and notational confusion between the explicit condition and the i...
Pei Wang
AI
2011
Springer
14 years 6 months ago
First-order logical filtering
Logical filtering is the process of updating a belief state (set of possible world states) after a sequence of executed actions and perceived observations. In general, it is intr...
Afsaneh Shirazi, Eyal Amir
ACSAC
2000
IEEE
15 years 4 months ago
Enabling Secure On-Line DNS Dynamic Update
Domain Name System (DNS) is the system for the mapping between easily memorizable host names and their IP addresses. Due to its criticality, security extensions to DNS have been p...
Xunhua Wang, Yih Huang, Yvo Desmedt, David Rine