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» Adapting Mathematical Domain Reasoners
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GECCO
2011
Springer
276views Optimization» more  GECCO 2011»
12 years 10 months ago
Evolution of reward functions for reinforcement learning
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...
Scott Niekum, Lee Spector, Andrew G. Barto
SIGIR
2012
ACM
11 years 9 months ago
Automatic suggestion of query-rewrite rules for enterprise search
Enterprise search is challenging for several reasons, notably the dynamic terminology and jargon that are specific to the enterprise domain. This challenge is partly addressed by...
Zhuowei Bao, Benny Kimelfeld, Yunyao Li
PLDI
2009
ACM
14 years 1 months ago
Analyzing recursive programs using a fixed-point calculus
We show that recursive programs where variables range over finite domains can be effectively and efficiently analyzed by describing the analysis algorithm using a formula in a ...
Salvatore La Torre, Parthasarathy Madhusudan, Genn...
RSCTC
2000
Springer
197views Fuzzy Logic» more  RSCTC 2000»
13 years 10 months ago
Rough Set Approach to CBR
We discuss how Case Based Reasoning (CBR) (see e.g. [1], [4]) philosophy of adaptation of some known situations to new similar ones can be realized in rough set framework [5] for c...
Jan Wierzbicki
ICDCS
2011
IEEE
12 years 6 months ago
Delay-Cognizant Reliable Delivery for Publish/Subscribe Overlay Networks
—The number of real-world applications that require QoS guarantees is constantly increasing and they often follow the publish/subscribe (pub/sub) messaging paradigm, which provid...
Shuo Guo, Kyriakos Karenos, Minkyong Kim, Hui Lei,...