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POLICY
2005
Springer
13 years 10 months ago
Approximating Service Utility from Policies and Value Function Patterns
Service-oriented computing provides the right means for building flexible systems that allow dynamic configuration and on-the-fly composition. In order to realize this vision, ...
Steffen Lamparter, Daniel Oberle, Andreas Eberhart
TSMC
1998
132views more  TSMC 1998»
13 years 4 months ago
Decision support for vehicle dispatching using genetic programming
—Vehicle dispatching consists of allocating real-time service requests to a fleet of moving vehicles. In this paper, each vehicle is associated with a vector of attribute values...
Ilham Benyahia, Jean-Yves Potvin
ICML
2001
IEEE
14 years 5 months ago
Off-Policy Temporal Difference Learning with Function Approximation
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...
Doina Precup, Richard S. Sutton, Sanjoy Dasgupta
ATAL
2009
Springer
13 years 11 months ago
An empirical analysis of value function-based and policy search reinforcement learning
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
Shivaram Kalyanakrishnan, Peter Stone
INFOCOM
2010
IEEE
13 years 3 months ago
Utility Maximization for Delay Constrained QoS in Wireless
Abstract—This paper studies the problem of utility maximization for clients with delay based QoS requirements in wireless networks. We adopt a model used in a previous work that ...
I-Hong Hou, P. R. Kumar