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» Evolution and learning in multiagent systems
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AGENTS
2001
Springer
14 years 1 months ago
Adjustable autonomy in real-world multi-agent environments
Through adjustable autonomy (AA), an agent can dynamically vary the degree to which it acts autonomously, allowing it to exploit human abilities to improve its performance, but wi...
Paul Scerri, David V. Pynadath, Milind Tambe
CIIA
2009
13 years 10 months ago
Dynamic Scheduling in Petroleum Process using Reinforcement Learning
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...
Nassima Aissani, Bouziane Beldjilali
SENSYS
2010
ACM
13 years 6 months ago
Evolution and sustainability of a wildlife monitoring sensor network
As sensor network technologies become more mature, they are increasingly being applied to a wide variety of applications, ranging from agricultural sensing to cattle, oceanic and ...
Vladimir Dyo, Stephen A. Ellwood, David W. Macdona...
CORR
2010
Springer
185views Education» more  CORR 2010»
13 years 5 months ago
Analysing the behaviour of robot teams through relational sequential pattern mining
This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of...
Grazia Bombini, Raquel Ros, Stefano Ferilli, Ramon...
AOSE
2005
Springer
14 years 2 months ago
Aspects in Agent-Oriented Software Engineering: Lessons Learned
Several concerns in the development of multi-agent systems (MASs) cannot be represented in a modular fashion. In general, they inherently affect several system modules and cannot b...
Alessandro F. Garcia, Uirá Kulesza, Cl&aacu...