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AAAI
2011
14 years 3 months ago
Optimal Rewards versus Leaf-Evaluation Heuristics in Planning Agents
Planning agents often lack the computational resources needed to build full planning trees for their environments. Agent designers commonly overcome this finite-horizon approxima...
Jonathan Sorg, Satinder P. Singh, Richard L. Lewis
178
Voted
STOC
2006
ACM
244views Algorithms» more  STOC 2006»
16 years 3 months ago
Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
We introduce a new low-distortion embedding of d 2 into O(log n) p (p = 1, 2), called the Fast-Johnson-LindenstraussTransform. The FJLT is faster than standard random projections ...
Nir Ailon, Bernard Chazelle
MOBIHOC
2002
ACM
16 years 2 months ago
Approximating minimum size weakly-connected dominating sets for clustering mobile ad hoc networks
We present a series of approximation algorithms for finding a small weakly-connected dominating set (WCDS) in a given graph to be used in clustering mobile ad hoc networks. The st...
Yuanzhu Peter Chen, Arthur L. Liestman
APPROX
2008
Springer
127views Algorithms» more  APPROX 2008»
15 years 5 months ago
Approximating Single Machine Scheduling with Scenarios
In the field of robust optimization, the goal is to provide solutions to combinatorial problems that hedge against variations of the numerical parameters. This constitutes an effor...
Monaldo Mastrolilli, Nikolaus Mutsanas, Ola Svenss...
ICML
2004
IEEE
16 years 4 months ago
Convergence of synchronous reinforcement learning with linear function approximation
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Artur Merke, Ralf Schoknecht