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334views
14 years 6 months ago
Rollout Sampling Approximate Policy Iteration
Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schem...
Christos Dimitrakakis, Michail G. Lagoudakis
IJCAI
2007
13 years 10 months ago
Heuristic Selection of Actions in Multiagent Reinforcement Learning
This work presents a new algorithm, called Heuristically Accelerated Minimax-Q (HAMMQ), that allows the use of heuristics to speed up the wellknown Multiagent Reinforcement Learni...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
IJNM
2008
131views more  IJNM 2008»
13 years 9 months ago
Using temporal correlation for fault localization in dynamically changing networks
A mobile ad-hoc network creates a dynamic environment where node mobility can cause periodic changes in routes. Most existing fault localization algorithms assume availability of ...
Maitreya Natu, Adarshpal S. Sethi
CN
2000
108views more  CN 2000»
13 years 9 months ago
A Web marketing system with automatic pricing
: We propose a new scheme of `automatic pricing' for digital contents, and describe an implemented system as well as concrete pricing algorithms for it. Automatic pricing refe...
Naoki Abe, Tomonari Kamba
ITC
2002
IEEE
112views Hardware» more  ITC 2002»
14 years 2 months ago
Multiplets, Models, and the Search for Meaning: Improving Per-Test Fault Diagnosis
The advantage to “one test at a time” fault diagnosis is its ability to implicate the components of complicated defect behaviors. The disadvantage is the large size and opacit...
David B. Lavo, Ismed Hartanto, Tracy Larrabee