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PRICAI
2000
Springer
14 years 1 months ago
Generating Hierarchical Structure in Reinforcement Learning from State Variables
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...
Bernhard Hengst
EH
1999
IEEE
351views Hardware» more  EH 1999»
14 years 2 months ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
RAID
2010
Springer
13 years 8 months ago
Inferring Protocol State Machine from Real-World Trace
Application-level protocol specifications are helpful for network security management, including intrusion detection, intrusion prevention and detecting malicious code. However, c...
Yipeng Wang, Zhibin Zhang, Li Guo
NIPS
2007
13 years 11 months ago
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
We propose a method for reconstruction of human brain states directly from functional neuroimaging data. The method extends the traditional multivariate regression analysis of dis...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
EMNLP
2004
13 years 11 months ago
From Machine Translation to Computer Assisted Translation using Finite-State Models
State-of-the-art machine translation techniques are still far from producing high quality translations. This drawback leads us to introduce an alternative approach to the translat...
Jorge Civera, Elsa Cubel, Antonio L. Lagarda, Davi...