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» Managing Complexity in Large Learning Robotic Systems
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GECCO
2005
Springer
220views Optimization» more  GECCO 2005»
14 years 1 months ago
Scale invariant pareto optimality: a meta--formalism for characterizing and modeling cooperativity in evolutionary systems
This article describes a mathematical framework for characterizing cooperativity in complex systems subject to evolutionary pressures. This framework uses three foundational compo...
Mark Fleischer
BTW
2007
Springer
119views Database» more  BTW 2007»
14 years 1 months ago
Change Management in Large Information Infrastructures - Representing and Analyzing Arbitrary Metadata
Abstract: With information infrastructures getting more and more complex, it becomes necessary to give automated support for managing the evolution of the infrastructure. If change...
Boris Stumm, Stefan Dessloch
ICAS
2006
IEEE
157views Robotics» more  ICAS 2006»
14 years 1 months ago
Adaptive provisioning using virtual machines and autonomous role-based management
A modern server system must deliver a complex set of obligations towards its users. We study the concept of roles as autonomous encapsulations of a set of promises. Using virtuali...
Kyrre M. Begnum, Mark Burgess, John A. Sechrest
AIIA
2007
Springer
14 years 1 months ago
Reinforcement Learning in Complex Environments Through Multiple Adaptive Partitions
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...
IADIS
2004
13 years 9 months ago
New Perspectives on Teaching and Learning Software Systems Development in Large Groups - Telecollaboration
This paper outlines new perspectives on the teaching and learning of software systems development in large groups based on a newly designed, final year, Software Systems Analysis ...
Zenon Chaczko, David J. Davis, Craig Scott