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GECCO
2011
Springer
276views Optimization» more  GECCO 2011»
14 years 1 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
MM
2003
ACM
124views Multimedia» more  MM 2003»
15 years 3 months ago
Using structure patterns of temporal and spectral feature in audio similarity measure
Although statistical characteristics of audio features are widely used for similarity measure in most of current audio analysis systems and have been proved to be effective, they ...
Rui Cai, Lie Lu, HongJiang Zhang
ASE
2006
122views more  ASE 2006»
14 years 10 months ago
Combining Proof Plans with Partial Order Planning for Imperative Program Synthesis
The structured programming literature provides methods and a wealth of heuristic knowledge for guiding the construction of provably correct imperative programs. We investigate the...
Andrew Ireland, Jamie Stark
ICCD
1992
IEEE
126views Hardware» more  ICCD 1992»
15 years 2 months ago
High-Level State Machine Specification and Synthesis
Current synthesis methodologies based on hardwaredescription languages focus mainly on two distinct levels: behavior and register-transfer levels. In many practical cases, however...
Andreas Kuehlmann, Reinaldo A. Bergamaschi
GECCO
2006
Springer
185views Optimization» more  GECCO 2006»
15 years 1 months ago
Convergence to global optima for genetic programming systems with dynamically scaled operators
This work shows asymptotic convergence to global optima for a family of dynamically scaled genetic programming systems where the underlying population consists of a fixed number o...
Lothar M. Schmitt, Stefan Droste