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Keywords
(10)
Adaptation and Learning
Artificial Immune System
Clonal Selection
Distributed Architecture
Distributed Learning Environment
Immune System
Information Processing
Multiple Objectives
Parallel Processing
Spatial Distribution
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IIDLE: An Immunological Inspired Distributed Learning Environment for Multiple Objective and Hybrid Optimisation
IIDLE: An Immunological Inspired Distributed Learning Environment for Multiple Objective and Hybrid Optimisation,10.1109/CEC.2006.1688352,Jason Brownl
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IIDLE: An Immunological Inspired Distributed Learning Environment for Multiple Objective and Hybrid Optimisation
(
Citations: 6
)
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Jason Brownlee
The acquired
immune system
is a robust and powerful
information processing
system that demonstrates features such as decentralised control, parallel processing, adaptation, and learning. The immunological inspired
distributed learning environment
(IIDLE) is a
clonal selection
inspired
artificial immune system
(AIS) that exploits the inherent parallelism, decentralised control, spatially distributed nature, and learning behaviours of the immune system. The
distributed architecture
and modular process of the IIDLE framework are shown to be useful features on complex search and optimisation tasks in addition to facilitating some of the desired robustness of the inspiration.
Conference:
IEEE Congress on Evolutionary Computation - CEC
, 2006
DOI:
10.1109/CEC.2006.1688352
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Citation Context
(4)
...Some original and representative methods have been continually appeared in the literature (Coello Coello 2005;
Brownlee 2006;
Freschi et al. 2010; Campelo et al. 2007; Gong et al. 2008; Omkar et al. 2008; Tan et al. 2008; Zhang 2006, 2007; Luh et al. 2003; Xiao and Zu 2007), among which a few constraint-handling techniques were displayed for CMO, but difficult for DCMO (Zhang 2006, 2007; Luh et al. 2003; Xiao and Zu 2007)...
Zhuhong Zhang
,
et al.
Artificial immune system in dynamic environments solving time-varying ...
...Such work is strongly related to, and perhaps provides a general model for the previously proposed Immunological Inspired Distributed Learning Environment (IIDLE) [
1
]...
JASON BROWNLEE
.
Integration of the Pathogenic Exposure Paradigm and the Hierarchical I...
...This aligns with what the IIDLE intended to provide in its initial inception [
30
] (also see IIDLE vision11)...
JASON BROWNLEE
.
Unexplored Territory: Seeds For Future Research Investigations
...A machine learning platform inspired by the adaptive properties of the clonal selection theory, and the spatially distributed properties of the acquired immune system physiology has been proposed called the Immunological Inspired Distributed Learning Environment (IIDLE) [
7
]...
...Figure 2 - A summary of the design goals for the IIDLE (from [4] and [
7
])...
...The concern is that such a perspective does not match the proposed spirit of the project: computational intelligence in the field of artificial immune systems (as proposed in [
7
])...
...Experimental examples include the different TSP objectives [
7
], the different objective functions [5], or in the human operators assessing the aesthetics of solutions [6]...
...The generalise selection process allows a variety of different selectionist-based computational intelligence algorithms to be implemented ([3,
5-7
]) not limited to variations of the clonal selection algorithm, genetic algorithm, particle swarm, ant colony, random search, and learning vector quantisation...
...The redundancy of the system was investigated by removing entire localities of the system and observing the effect on learning [6,
7
]...
JASON BROWNLEE
.
A Review of the Immunological Inspired Distributed Learning Environmen...
References
(13)
Exploiting Parallelism Inherent in AIRS, an Artificial Immune Classifier
(
Citations: 31
)
Andrew Watkins
,
Jon Timmis
Conference:
International Conference on Artificial Immune Systems - ICARIS
, pp. 427-438, 2004
PARALLELIZING AN IMMUNE-INSPIRED ALGORITHM FOR EFFICIENT PATTERN RECOGNITION
(
Citations: 20
)
ANDREW WATKINS
,
XINTONG BI
,
AMIT PHADKE
Genetic Algorithms in Search Optimization and Machine Learning
(
Citations: 17426
)
David E. Goldberg
Published in 1989.
Immunology : A Short Course
(
Citations: 91
)
R. Coico
,
G Sunshine
,
E. Benjamini
Published in 2003.
The Traveling Salesman, Computational Solutions for TSP Applications
(
Citations: 242
)
Gerhard Reinelt
Published in 1994.
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Citations
(6)
Artificial immune system in dynamic environments solving time-varying non-linear constrained multi-objective problems
Zhuhong Zhang
,
Shuqu Qian
Journal:
Soft Computing - SOCO
, vol. 15, no. 7, pp. 1333-1349, 2011
A Hierarchical Framework of the Acquired Immune System
(
Citations: 4
)
JASON BROWNLEE
Published in 2007.
Integration of the Pathogenic Exposure Paradigm and the Hierarchical Immune System Framework
(
Citations: 3
)
JASON BROWNLEE
Published in 2007.
Unexplored Territory: Seeds For Future Research Investigations
JASON BROWNLEE
Published in 2007.
A Review of the Immunological Inspired Distributed Learning Environment
JASON BROWNLEE
Published in 2007.