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ROBOCUP
2000
Springer
130views Robotics» more  ROBOCUP 2000»
15 years 10 months ago
Improvement Continuous Valued Q-learning and Its Application to Vision Guided Behavior Acquisition
Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to re...
Yasutake Takahashi, Masanori Takeda, Minoru Asada
MICRO
1995
IEEE
217views Hardware» more  MICRO 1995»
15 years 10 months ago
Improving instruction-level parallelism by loop unrolling and dynamic memory disambiguation
Exploitation ofinstruction-levelparallelism is an ejfective mechanism for improving the performance of modern super-scalar/VLIW processors. Various software techniques can be appl...
Jack W. Davidson, Sanjay Jinturkar
CONEXT
2008
ACM
15 years 8 months ago
TCP improvement in multi-radio multi-channel multi-hop networks
In this paper, we seek to enhance the poor performance of original TCP in wireless multi-hop environments due to the intra-flow contention between TCP-DATA and TCP-ACK packets. As...
Xiaofei Wang, Taekyoung Kwon, Yanghee Choi
EVOW
2008
Springer
15 years 8 months ago
Multiobjective Prototype Optimization with Evolved Improvement Steps
Recently, a new iterative optimization framework utilizing an evolutionary algorithm called "Prototype Optimization with Evolved iMprovement Steps" (POEMS) was introduced...
Jirí Kubalík, Richard Mordinyi, Stef...
ESANN
2008
15 years 8 months ago
Improvement in Game Agent Control Using State-Action Value Scaling
The aim of this paper is to enhance the performance of a reinforcement learning game agent controller, within a dynamic game environment, through the retention of learned informati...
Leo Galway, Darryl Charles, Michaela M. Black