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ATAL
2005
Springer
13 years 11 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
ICCD
2008
IEEE
192views Hardware» more  ICCD 2008»
14 years 2 months ago
Energy-aware opcode design
— Embedded processors are required to achieve high performance while running on batteries. Thus, they must exploit all the possible means available to reduce energy consumption w...
Balaji V. Iyer, Jason A. Poovey, Thomas M. Conte
DAC
1998
ACM
13 years 9 months ago
Synthesis of Power-Optimized and Area-Optimized Circuits from Hierarchical Behavioral Descriptions
We present a technique for synthesizing power- as well as area-optimized circuits from hierarchical data flow graphs under throughput constraints. We allow for the use of complex...
Ganesh Lakshminarayana, Niraj K. Jha
AAAI
2008
13 years 7 months ago
Resource Constrained Distributed Constraint Optimization with Virtual Variables
Cooperative problem solving with resource constraints are important in practical multi-agent systems. Resource constraints are necessary to handle practical problems including dis...
Toshihiro Matsui, Hiroshi Matsuo, Marius Silaghi, ...
AIPS
2009
13 years 6 months ago
Flexible Execution of Plans with Choice
Dynamic plan execution strategies allow an autonomous agent to respond to uncertainties while improving robustness and reducing the need for an overly conservative plan. Executive...
Patrick R. Conrad, Julie A. Shah, Brian C. William...