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ICAI
2003
15 years 8 months ago
A Quantitative Model of Capabilities in Multi-Agent Systems
Reasoning about capabilities in multi-agent systems is crucial for many applications. There are two aspects of reasoning about the capabilities of an agent to achieve its goals. O...
Linli He, Thomas R. Ioerger
VLSID
2002
IEEE
151views VLSI» more  VLSID 2002»
16 years 7 months ago
Mode Selection and Mode-Dependency Modeling for Power-Aware Embedded Systems
Among the many techniques for system-level power management, it is not currently possible to guarantee timing constraints and have a comprehensive system model at the same time. S...
Dexin Li, Pai H. Chou, Nader Bagherzadeh
CP
2004
Springer
16 years 4 days ago
Heuristic Selection for Stochastic Search Optimization: Modeling Solution Quality by Extreme Value Theory
The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...
Vincent A. Cicirello, Stephen F. Smith
222
Voted
CC
2008
Springer
193views System Software» more  CC 2008»
15 years 8 months ago
Automatic Transformations for Communication-Minimized Parallelization and Locality Optimization in the Polyhedral Model
The polyhedral model provides powerful abstractions to optimize loop nests with regular accesses. Affine transformations in this model capture a complex sequence of execution-reord...
Uday Bondhugula, Muthu Manikandan Baskaran, Sriram...
AI
1998
Springer
15 years 6 months ago
Model-Based Average Reward Reinforcement Learning
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
Prasad Tadepalli, DoKyeong Ok