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» How to Dynamically Merge Markov Decision Processes
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78
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GLOBECOM
2008
IEEE
15 years 4 months ago
Cross-Layer Design of Optimal Adaptation Technique over Selection-Combining Diversity Nakagami-m Fading Channels
— Adaptive modulation and antenna diversity are two important enabling techniques for future wireless network to meet demand for high data rate transmission. We study a Markov de...
Ashok K. Karmokar, Vijay K. Bhargava
81
Voted
SEKE
2004
Springer
15 years 3 months ago
Application Semiotics Engineering Process
As application semantics becomes more complex and dynamic in IT systems, it is necessary to engineer the application semantics in its own lifecycle of development parallel to syste...
Gang Zhao
72
Voted
NIPS
2004
14 years 11 months ago
Approximately Efficient Online Mechanism Design
Online mechanism design (OMD) addresses the problem of sequential decision making in a stochastic environment with multiple self-interested agents. The goal in OMD is to make valu...
David C. Parkes, Satinder P. Singh, Dimah Yanovsky
AIPS
2000
14 years 11 months ago
Representations of Decision-Theoretic Planning Tasks
Goal-directed Markov Decision Process models (GDMDPs) are good models for many decision-theoretic planning tasks. They have been used in conjunction with two different reward stru...
Sven Koenig, Yaxin Liu
AAAI
1996
14 years 11 months ago
Rewarding Behaviors
Markov decision processes (MDPs) are a very popular tool for decision theoretic planning (DTP), partly because of the welldeveloped, expressive theory that includes effective solu...
Fahiem Bacchus, Craig Boutilier, Adam J. Grove