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ATAL
2004
Springer
15 years 3 months ago
Analysis of a Stochastic Model of Adaptive Task Allocation in Robots
Adaptation is an essential requirement for self–organizing multi–agent systems functioning in unknown dynamic environments. Adaptation allows agents, e.g., robots, to change th...
Aram Galstyan, Kristina Lerman
ENC
2006
IEEE
15 years 1 months ago
Adaptive Node Refinement Collocation Method for Partial Differential Equations
In this work, by using the local node refinement technique purposed in [2, 1], and a quad-tree type algorithm [3, 13], we built a global refinement technique for Kansa's unsy...
José Antonio Muñoz-Gómez, Ped...
IJCAI
2007
14 years 11 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
HPDC
2010
IEEE
14 years 11 months ago
A hybrid Markov chain model for workload on parallel computers
This paper proposes a comprehensive modeling architecture for workloads on parallel computers using Markov chains in combination with state dependent empirical distribution functi...
Anne Krampe, Joachim Lepping, Wiebke Sieben
CDC
2010
IEEE
128views Control Systems» more  CDC 2010»
14 years 4 months ago
Greedy sensor selection: Leveraging submodularity
ACT We consider the problem of sensor selection in resource constrained sensor networks. The fusion center selects a subset of k sensors from an available pool of m sensors accordi...
Manohar Shamaiah, Siddhartha Banerjee, Haris Vikal...