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ECML
2004
Springer
14 years 1 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner
ICESS
2004
Springer
14 years 1 months ago
Selecting a Scheduling Policy for Embedded Real-Time Monitor and Control Systems
An integrated solution to guarantee real-time requirements in embedded real-time monitor and control systems is presented in this paper. First l task model is abstracted from such ...
Qingxu Deng, Mingsong Lv, Ge Yu
BROADNETS
2004
IEEE
13 years 11 months ago
Policy-Based Hybrid Hierarchical Optical Networks
This document presents provisioning strategies for emerging hybrid optical networks. The idea is to make use of policy-based management that guides the behavior of a network throu...
Belkacem Daheb, Wissam Fawaz, Olivier Audouin, Bel...
PPPJ
2004
ACM
14 years 1 months ago
Embedding JAAS in agent roles to apply local security policies
Agents are an emerging technology that grants programmers a new way to exploit distributed resources. Roles are a powerful concept that can be used to model agent interactions, all...
Giacomo Cabri, Luca Ferrari, Letizia Leonardi
APIN
2004
81views more  APIN 2004»
13 years 7 months ago
Learning Generalized Policies from Planning Examples Using Concept Languages
In this paper we are concerned with the problem of learning how to solve planning problems in one domain given a number of solved instances. This problem is formulated as the probl...
Mario Martin, Hector Geffner