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GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
15 years 10 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
IPSN
2004
Springer
15 years 12 months ago
Lattice sensor networks: capacity limits, optimal routing and robustness to failures
We study network capacity limits and optimal routing algorithms for regular sensor networks, namely, square and torus grid sensor networks, in both, the static case (no node failu...
Guillermo Barrenechea, Baltasar Beferull-Lozano, M...
CORR
2008
Springer
175views Education» more  CORR 2008»
15 years 6 months ago
Energy Aware Self-Organizing Density Management in Wireless Sensor Networks
Energy consumption is the most important factor that determines sensor node lifetime. The optimization of wireless sensor network lifetime targets not only the reduction of energy...
Erwan Le Merrer, Vincent Gramoli, Anne-Marie Kerma...
ISPDC
2010
IEEE
15 years 5 months ago
Practical Uniform Peer Sampling under Churn
—Providing independent uniform samples from a system population poses considerable problems in highly dynamic settings, like P2P systems, where the number of participants and the...
Roberto Baldoni, Marco Platania, Leonardo Querzoni...
ICNP
2006
IEEE
16 years 19 days ago
Benefit-based Data Caching in Ad Hoc Networks
—Data caching can significantly improve the efficiency of information access in a wireless ad hoc network by reducing the access latency and bandwidth usage. However, designing e...
Bin Tang, Himanshu Gupta, Samir R. Das