Sección De Computación, Hussein A. Abbass, Peter J. Fleming, Eckart Zitzler, Lothar Thiele, ...
1998. IEE. [7] M.A. Abido. A new multiobjective evolutionary algorithm for environmental/economic
Strategic Positioning in Tactical Scenario Planning (2009)
Whitacre, James M., Abbass, Hussein A., Sarker, Ruhul, Bender, Axel, Baker, Stephen
Capability planning problems are pervasive throughout many areas of human interest with prominent examples found in defense and security. Planning provides a unique context for optimization that has...
Localization and Fitness Inheritance in Solving Noisy Multi-objective Optimization Problems (2009)
Lam T. Bui, Hussein A. Abbass, Daryl Essam, Lam T. Bui, Hussein A. Abbass, Daryl Essam
This paper investigates the use of local models in the context of noisy evolutionary multi-objective optimization. Within this technique, the search space is explicitly divided into several...
Hai H. Dam, Hussein H. Abbass, Chris Lokan, Hai H. Dam, Hussein A. Abbass, Chris Lokan
XCS is widely accepted as one of the most reliable Michigan-style Learning Classifier System for data mining. Many studies found that XCS is able to provide good generalization using a ternary...
Real Time Signature Extraction From a Supervised Classifier System (2008)
Kamran Shafi, Hussein A. Abbass, Senior Member, Weiping Zhu
Abstract — Recently some algorithms have been proposed to clean post-training rule populations evolved by XCS, a state of the art Learning Classifier System (LCS). We present an algorithm to...
Performance Analysis of Elitism in Multi-objective Ant Colony Optimization Algorithms (2008)
Lam T. Bui, James Whitacre, Hussein A. Abbass, Lam T. Bui, James Whitacre, Hussein A. Abbass
This paper investigates the effect of elitism on multi-objective ant colony optimization algorithms (MACOs). We use a straightforward and systematic approach in this investigation with elitism...
Ants Guide Future Pilots (2008)
Sameer Alam, Minh-ha Nguyen, Hussein A. Abbass, Michael Barlow, Sameer Alam, Minh-ha Nguyen, ...
In this paper an Ant Colony Optimization (ACO) approach is extended to the safety and time critical domain of air traffic management. This approach is used to generate a set of safe weather avoidance...
Neural-Based Learning Classifier Systems (2008)
Hai H. Dam, Hussein A. Abbass, Chris Lokan, Xin Yao, Hai H. Dam, Hussein A. Abbass, ...
UCS is a supervised learning classifier system that was introduced in 2003 for classification in data mining tasks. The representation of a rule in UCS as a univariate classification rule is...
Risk Assessment of Capability Requirements Using WISDOM–II (2008)
Ang Yang, Hussein A. Abbass, Ruhul Sarker, Ang Yang, Hussein A. Abbass, Ruhul Sarker
The analysis of capability requirements plays a very important role in military operations. It assists analysts to make decisions at strategic, operational and tactical levels. The analysis of...
Land Combat Scenario Planning: A Multiobjective Approach (2008)
Ang Yang, Hussein A. Abbass, Ruhul Sarker, Ang Yang, Hussein A. Abbass, Ruhul Sarker
The simulation of land combat operations is a complex task. The space of possibilities is exponential and the performance criteria are usually in conflict; thus finding a sweet spot in this complex...
Neural evolution for collision detection & resolution in a 2d free flight environment (2008)
Sameer Alam, Sameer Alam, Michelle Mcpartl, Michelle Mcpartl, Michael Barlow, Michael Barlow, ...
During the last decade, air traffic movements worldwide have experienced a tremendous growth. Future air traffic management concepts such as Free Flight have been proposed to provide a means by which...
Network Centric Multi-Agent Systems: A Novel Architecture (2008)
Ang Yang, Hussein A. Abbass, Ruhul Sarker, Michael Barlow, Ang Yang, Hussein A. Abbass, ...
Complex adaptive systems (CAS) is the study of many interacting components, where the interaction is governed by simple rules while the overall behavior of the system exhibits certain level of...
Lam T. Bui, Kalyanmoy Deb, Hussein A. Abbass, Daryl Essam, Lam T. Bui, Kalyanmoy Deb, ...
In this paper, we propose a framework using local models for multi-objective optimization to guide the search heuristic in both the decision and objective spaces. The localization is built using a...
NCMAA: a Network Centric Multi-Agent Architecture for Modelling Complex Adaptive Systems (2008)
Ang Yang, Neville J. Curtis, Hussein A. Abbass, Ruhul Sarker, Ang Yang, Neville J. Curtis, ...
Complex adaptive systems (CAS) is the study of many nonlinearly interacting components, where the interaction is governed by simple rules, while the overall behavior of the system exhibits certain...
Can Evolutionary Computation Handle Large (2008)
Hai H. Dam, Kamran Shafi, Hussein A. Abbass, Hai H. Dam, Kamran Shafi, Hussein A. Abbass
Evolutionary Learning Classifier Systems (ELCS) were introduced by Holland a few decades ago. Since their birth, they were successfully applied to various data analysis domains. XCS is currently...
Lam T. Bui, Jürgen Branke, Hussein A. Abbass, Lam T. Bui, Jürgen Branke, Hussein Abbass
Multi-objective optimization for dynamic environments
Evolutionary Online Data Mining An Investigation in a Dynamic Environment (2008)
Hai H. Dam, Hussein A. Abbass, Chris Lokan, Hai H. Dam, Hussein A. Abbass, Chris Lokan
Recently, traditional data mining algorithms are challenged by two problems: streaming data, and changes in the hidden context. These challenges emerged from real-world applications such as network...
Lam T. Bui, Hussein A. Abbass, Daryl Essam, Lam T. Bui, Hussein A. Abbass, Daryl Essam
genotype-phenotype mapping to solve highly
ATOMS: Air Traffic Operations and Management Simulator (2008)
Sameer Alam, Hussein A. Abbass, Michael Barlow, Sameer Alam, Hussein A. Abbass, Michael Barlow
In this paper we introduce ATOMS (Air Traffic Operations & Management Simulator) which is an air traffic and airspace modeling and simulation system for the analysis of Free Flight concepts. This...
multi–objective optimization methods (2008)
Lam T. Bui, Daryl Essam, Hussein A. Abbass, David Green
Performance analysis of evolutionary
Lam T. Bui, Daryl Essam, Hussein A. Abbass, David Green, Lam T. Bui, Daryl Essam, ...
in noisy environments
Domain Ontology Guided Feature-Selection for Document Categorization (2008)
Bill B. Wang, Hussein A. Abbass, Michael Barlow
Abstract:We present a novel method employing a hierarchical domain ontology structure to select features representing documents. All raw words in the training documents are mapped to concepts in a...
Australian Defence Force Academy, (2008)
Abstract- In this paper, we present a comparison between two multi-objective formulations to the formation of neuro-ensembles. The first formulation splits the training set into two non-overlapping...
Is a Self-Adaptive Pareto Approach Beneficial for Controlling Embodied Virtual Robots? (2008)
Abstract. A self-adaptive Pareto Evolutionary Multi-objective Optimization (EMO) algorithm is proposed for evolving controllers for a virtually embodied robot. The main contribution of the...
Analysis of CCME: Coevolutionary Dynamics, Automatic Problem Decomposition and (2008)
Minh Ha Nguyen, Hussein A. Abbass, Senior Member, Robert I, Senior Fellow
Abstract — In most real-world problems, we either know little about the problems or the problems are too complex to have a clear vision on how to decompose them by hand. Thus, it is usually...
Australian Defence Force Academy Campus (2008)
Anti–correlation has been used in training neural network ensembles. Negative correlation learning (NCL) is the state of the art anti–correlation measure. We present an alternative...
Domain Ontology Guided Feature-Selection for Document Categorization Abstract (2008)
Bill B. Wang, Hussein A. Abbass, Michael Barlow
We present a novel method employing a hierarchical domain ontology structure to select features representing documents. All raw words in the training documents are mapped to concepts in a domain...
The application of evolutionary computation for designing and generating artificial creatures such as robots and virtual organisms have become an important endeavor in artificial life and robotics...
Li, Xiaodong, Kirley, Michael, Zhang, Mengjie, Green, David, Ciesielski, Vic, Abbass, Hussein A., ...
This volume constitutes the proceedings of the 7th International Conference on Simulated Evolution and Learning, SEAL 2008, held in Melbourne, Australia, during December 7-10, 2008. The 65 papers...
Li, Xiaodong, Kirley, Michael, Zhang, Mengjie, Green, David, Ciesielski, Vic, Abbass, Hussein A., ...
This volume constitutes the proceedings of the 7th International Conference on Simulated Evolution and Learning, SEAL 2008, held in Melbourne, Australia, during December 7-10, 2008. The 65 papers...
Li, Xiaodong, Kirley, Michael, Zhang, Mengjie, Green, David, Ciesielski, Vic, Abbass, Hussein A., ...
This volume constitutes the proceedings of the 7th International Conference on Simulated Evolution and Learning, SEAL 2008, held in Melbourne, Australia, during December 7-10, 2008. The 65 papers...
Constraint Logic Programming for Chemical Process Synthesis (2007)
Hussein A. Abbass, Geraint A. Wiggins, Ramachandran Lakshmanan, Bill Morton
We present a successful application of Constraint Logic Programming (CLP) to a major problem in Chemical Process Synthesis: the retrofit of heat exchanger networks. The method combines expert...
Abstract A Comparative Study for Domain Ontology Guided Feature Extraction (2007)
Bill B. Wang, Hussein A. Abbass, Michael Barlow
We introduced a novel method employing a hierarchical domain ontology structure to extract features representing documents in our previous publication (Wang 2002). All raw words in the training...
TRADING-OFF MIND COMPLEXITY AND LOCOMOTION IN VIRTUALLY EMBODIED QUADRUPED ROBOT (2007)
plastic individuals that are able to adapt both through evolu-This paper investigates the use of a multi-objective approach tion and lifetime learning [7, 8, 16]. However, the artificial for evolving...
Australian Defence Force Academy Campus (2007)
Anti--correlation has been used in training neural network ensembles. Negative correlation learning (NCL) is the state of the art anti--correlation measure. We propose an alternative...
Hussein A. Abbass, Geraint A. Wiggins, Ramachandran Lakshmanan, Bill Morton
We present a successful application of Constraint Logic Programming (CLP) to a major problem in Chemical Process Synthesis: the retrofit of heat exchanger networks. The method combines expert...
How Multi-Objectivity Can Characterize The Complexities of Artificial Creatures (2007)
Jason Teo, Jason Teo, Hussein A. Abbass, Hussein A. Abbass
This paper proposes a novel perspective to the use of evolutionary multiobjective optimization (EMO) as a paradigm for the characterization of complexity. Our objective is not to introduce a new...
Australian Defence Force Academy Campus (2007)
Anti–correlation has been used in training neural network ensembles. Negative correlation learning (NCL) is the state of the art anti–correlation measure. An alternative anti–correlation...
WISDOM-II: A Network Centric Model for Warfare (2006)
Yang, Ang, Curtis, Neville, Abbass, Hussein A., Sarker, Ruhul, Barlow, Michael
Chapter 8 of 'Complex Science for a Complex World: Exploring Human Ecosystems with Agents'
The role of early stopping and population size in xcs for intrusion detection (2006)
Kamran Shafi, Hussein Abbass, Weiping Zhu, Kamran Shafi, Hussein A. Abbass
Evolutionary Learning Classifier Systems (LCSs) are rule based systems that have been used effectively in concept learning. XCS is a prominent LCS that uses genetic algorithms and reinforcement...
Sameer Alam, Sameer Alam, Hussein A. Abbass, Hussein A. Abbass, Michael Barlow, Michael Barlow
Free flight air traffic management is a paradigm shift to move the decision making process for route choices from air traffic controllers to the cockpit. It provides a unique opportunity to optimize...
Pareto meta-heuristics for generating safe flight trajectories under weather hazards (2006)
Sameer Alam, Sameer Alam, Lam T. Bui, Lam T. Bui, Hussein A. Abbass, Hussein A. Abbass, ...
This paper compares ant colony optimization (ACO) and evolutionary multi-objective optimization (EMO) for the weather avoidance in a free flight environment. The problem involves a number of...
Sameer Alam, Hussein A. Abbass, Michael Barlow, Peter Lindsay, Free Flight Airspace, Sameer Alam, ...
The continuing growth of air traffic worldwide motivates the need for new approaches to air traffic management that are more flexible both in terms of traffic volume and weather. Free Flight is one...
Sub-structural niching in estimation of distribution algorithms (2005)
Kumara Sastry, Hussein A. Abbass, David E. Goldberg, D. D. Johnson
We propose a sub-structural niching method that fully exploits the problem decomposition capability of linkagelearning methods such as the estimation distribution algorithms and concentrate on...
R.: WISDOM-II: A network centric model for warfare (2005)
Ang Yang, Ang Yang, Hussein A. Abbass, Hussein A. Abbass, Ruhul Sarker, Ruhul Sarker
With recognition of warfare as a complex adaptive system, a number of agent based distillation systems for warfare have been developed and adopted to study the dynamics of warfare and gain insight...
Dxcs: an xcs system for distributed data mining (2005)
Hussein H. Abbass, Hai H. Dam, Hai H. Dam, Hussein A. Abbass, Chris Lokan, Chris Lokan
XCS is a flexible system for data mining due to its ability to deal with environmental changes, learn online with little prior knowledge and evolve accurate and maximally general classifiers. In this...
Sub-structural niching in estimation of distribution algorithms (2005)
Kumara Sastry, Kumara Sastry, Hussein A. Abbass, Hussein A. Abbass, David E. Goldberg, David E. Goldberg, ...
We propose a sub-structural niching method that fully exploits the problem decomposition capability of linkage-learning methods such as the estimation of distribution algorithms and concentrate on...
Fitness inheritance for noisy evolutionary multi-objective optimization (2005)
Lam T. Bui, Lam T. Bui, Hussein A. Abbass, Hussein A. Abbass, Daryl Essam, Daryl Essam
This paper compares the performance of anti-noise methods, particularly probabilistic and re-sampling methods, using NSGA2. It then proposes a computationally less expensive approach to counteracting...
Hussein A. Abbass, Kumara Sastry, David E. Goldberg, Hussein A. Abbass, Kumara Sastry, David Goldberg
Genetic algorithms (GAs) that solve hard problems quickly, reliably and accurately are called competent GAs. When the fitness landscape of a problem changes overtime, the problem is called...
Complex 2004 Proceedings of the 7th Asia-Pacific Conference on Complex Systems (2004)
James Watson, Hussein A. Abbass, Chris Lokan, Peter Lindsay
Software engineering for artificial life, complex systems, and agent-based distillation
Differential Evolution for Solving Multi-Objective Optimization Problems (2004)
Ruhul Sarker, Hussein A. Abbass
The use of evolutionary strategies (ESs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population based...
Sub-structural niching in non-stationary environments (2004)
David E. Goldberg, Kumara Sastry, Kumara Sastry, Hussein A. Abbass, Hussein A. Abbass, David Goldberg
Niching enables a genetic algorithm (GA) to maintain diversity in a population. It is particularly useful when the problem has multiple optima where the aim is to £nd all or as many as possible of...
Online Adaptation in Learning Classifier Systems: Stream Data Mining (2004)
Hussein A. Abbass, Jaume Bacardit, Martin V. Butz, Xavier Llorà, Hussein A. Abbass, Jaume Bacardit, ...
In data mining, concept drift refers to the phenomenon that the underlying model (or concept) is changing over time. The aim of this paper is twofold. First, we propose a fundamental characterization...
Genetic Algorithms for a Large Scale Dynamic Allocation Problem (2003)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius
Mate-selection is the problem of deciding which animal should be culled and which should be mated in a breeding program. In addition, if the animal is to be mated, which animal from the other sex...
Genetic Algorithms for a Large Scale Dynamic Allocation Problem (2003)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius
Mate-selection is the problem of deciding which animal should be culled and which should be mated in a breeding program. In addition, if the animal is to be mated, which animal from the other sex...
Genetic Algorithms for a Large Scale Dynamic Allocation Problem (2003)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius
Mate-selection is the problem of deciding which animal should be culled and which should be mated in a breeding program. In addition, if the animal is to be mated, which animal from the other sex...
Genetic Algorithms for a Large Scale Dynamic Allocation Problem (2003)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius
Mate-selection is the problem of deciding which animal should be culled and which should be mated in a breeding program. In addition, if the animal is to be mated, which animal from the other sex...
Genetic Algorithms for a Large Scale Dynamic Allocation Problem (2003)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius
Mate-selection is the problem of deciding which animal should be culled and which should be mated in a breeding program. In addition, if the animal is to be mated, which animal from the other sex...
Genetic Algorithms for a Large Scale Dynamic Allocation Problem (2003)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius
Mate-selection is the problem of deciding which animal should be culled and which should be mated in a breeding program. In addition, if the animal is to be mated, which animal from the other sex...
Genetic Algorithms for a Large Scale Dynamic Allocation Problem (2003)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius
Mate-selection is the problem of deciding which animal should be culled and which should be mated in a breeding program. In addition, if the animal is to be mated, which animal from the other sex...
Searching under multi-evolutionary pressures (2003)
Hussein A. Abbass, Kalyanmoy Deb
Abstract. A number of authors made the claim that a multiobjective approach preserves genetic diversity better than a single objective approach. Sofar, none of these claims presented a thorough...
Search space difficulty of evolutionary neurocontrolled legged robots (2003)
Submitted to the 6 th Australia-Japan Joint Workshop on Intelligent and Evolutionary Systems The application of evolutionary computation for designing and generating artificial creatures such as...
A True Annealing Approach to the Marriage in Honey-Bees Optimization Algorithm (2003)
Marriage in Honey Bees Optimization (MBO) is a new swarm intelligence technique inspired by the marriage process of honey bees. It has been shown to be very effective in solving the propositional...
Multi-objectivity as a tool for constructing hierarchical complexity (2003)
Jason Teo, Minh Ha Nguyen, Hussein A. Abbass
Abstract. This paper presents a novel perspective to the use of multiobjective optimization and in particular evolutionary multi-objective optimization (EMO) as a measure of complexity. We show that...
Neuro-Morpho Evolution: What will happen if our body is not symmetric? (2003)
Jason Teo, Hussein A. Abbass, Kota Kinabalu
In this study, we evolve both the controller and morphology of artificially embodied legged creatures. This is achieved by relaxing certain morphological constraints previously imposed on the...
Genetic Algorithms for a Large Scale Dynamic Allocation Problem (2003)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius
Mate-selection is the problem of deciding which animal should be culled and which should be mated in a breeding program. In addition, if the animal is to be mated, which animal from the other sex...
Genetic Algorithms for a Large Scale Dynamic Allocation Problem (2003)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius
Mate-selection is the problem of deciding which animal should be culled and which should be mated in a breeding program. In addition, if the animal is to be mated, which animal from the other sex...
A Markov Chain Tabu Search Approach to the evolutionary allocation problem (2002)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius, Diederich, Joachim
The principal aim is to examine selected recent research in and applications of Operational Research/Management Science. Provides opportunities for exploring synergies and interfaces that exist...
A Markov Chain Tabu Search Approach to the evolutionary allocation problem (2002)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Diederich, J.
The principal aim is to examine selected recent research in and applications of Operational Research/Management Science. Provides opportunities for exploring synergies and interfaces that exist...
A Markov Chain Tabu Search Approach to the evolutionary allocation problem (2002)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius, Diederich, Joachim
The principal aim is to examine selected recent research in and applications of Operational Research/Management Science. Provides opportunities for exploring synergies and interfaces that exist...
A Markov Chain Tabu Search Approach to the evolutionary allocation problem (2002)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius, Diederich, Joachim
The principal aim is to examine selected recent research in and applications of Operational Research/Management Science. Provides opportunities for exploring synergies and interfaces that exist...
A Markov Chain Tabu Search Approach to the evolutionary allocation problem (2002)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius, Diederich, Joachim
The principal aim is to examine selected recent research in and applications of Operational Research/Management Science. Provides opportunities for exploring synergies and interfaces that exist...
A Markov Chain Tabu Search Approach to the evolutionary allocation problem (2002)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius, Diederich, Joachim
The principal aim is to examine selected recent research in and applications of Operational Research/Management Science. Provides opportunities for exploring synergies and interfaces that exist...
A Markov Chain Tabu Search Approach to the evolutionary allocation problem (2002)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius, Diederich, Joachim
The principal aim is to examine selected recent research in and applications of Operational Research/Management Science. Provides opportunities for exploring synergies and interfaces that exist...
Multi-objectivity for brain-behavior evolution of a physically-embodied organism (2002)
In this paper, we present a pareto multi–objective approach for evolving the behavior and brain (an artificial neural network (ANN)) of embodied artificial creatures. We will attempt to...
Mining Evolution Through Visualization (2002)
Michael Barlow, John Galloway, Hussein A. Abbass
Evolutionary computation works in high–dimensional search spaces. Understanding how evolution acts on these spaces is a key step not only to understanding how the system functions, but also to give...
Multi-objectivity for brain-behavior evolution of a physically-embodied organism (2002)
In this paper, we present a pareto multi–objective approach for evolving the behavior and brain (an artificial neural network (ANN)) of embodied artificial creatures. We will attempt to...
Trading-off Mind Complexity and Locomotion in a Physically Simulated Quadruped (2002)
This paper investigates the use of a multi-objective approach for evolving artificial neural networks that act as controllers for the legged locomotion of a 3-dimensional, artificial quadruped...
Coordination and synchronization of locomotion in a virtual robot (2002)
multaneously [8, 11, 14, 18]. Some work has also been carried out in evolving morphology alone [6] and evolving mor-This paper investigates the use of a multi-objective approach phology with a fixed...
AntTAG: A new method to compose computer programs using colonies of ants (2002)
Hussein A. Abbass, Xuan Hoai, Robert I. Mckay
Abstract-Genetic Programming (GP) plays the primary role for the discovery of programs through evolving the program’s set of parse trees. In this paper, we present a new technique for constructing...
The Self-Adaptive Pareto Differential Evolution Algorithm (2002)
Abstract-The Pareto Differential Evolution (PDE) algorithm was introduced last year and showed competitive results. The behavior of PDE, as in many other evolutionary multiobjective optimization...
Mining Evolution Through Visualization (2002)
Michael Barlow, John Galloway, Hussein A. Abbass
Evolutionary computation works in high–dimensional search spaces. Understanding how evolution acts on these spaces is a key step not only to understanding how the system functions, but also to give...
An evolutionary artificial neural network approach for breast cancer diagnosis (2002)
This paper presents an evolutionary artificial neural network approach based on the pareto differential evolution algorithm augmented with local search for the prediction of breast cancer. The...
Learning Text Classifier using the Domain Concept Hierarchy (2002)
Bill B. Wang, Hussein A. Abbass, Michael Barlow
Abstract: Automatic text categorization is an important component in many information organization and management tasks. Many researches have shown that similarity based categorization algorithms...
Coordination and synchronization of locomotion in a virtual robot (2002)
This paper investigates the use of a multi-objective approach for evolving artificial neural networks that act as controllers for the legged locomotion of a 3-dimensional, artificial quadruped...
Multi-objectivity for brain-behavior evolution of a physically-embodied organism (2002)
In this paper, we present a pareto multi–objective approach for evolving the behavior and brain (an artificial neural network (ANN)) of embodied artificial creatures. We will attempt to...
A Markov Chain Tabu Search Approach to the evolutionary allocation problem (2002)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius, Diederich, Joachim
The principal aim is to examine selected recent research in and applications of Operational Research/Management Science. Provides opportunities for exploring synergies and interfaces that exist...
A Markov Chain Tabu Search Approach to the evolutionary allocation problem (2002)
Abbass, Hussein A., Towsey, Michael W., Kozan, Erhan, Van Der Werf, Julius, Diederich, Joachim
The principal aim is to examine selected recent research in and applications of Operational Research/Management Science. Provides opportunities for exploring synergies and interfaces that exist...
C-Net: a method for generating non-deterministic and dynamic multivariate decision trees (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D.
Despite the fact that artificial neural networks (ANNs) are universal function approximators, their black box nature (that is, their lack of direct interpretability or expressive power) limits their...
C-Net: a method for generating non-deterministic and dynamic multivariate decision trees (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D.
Despite the fact that artificial neural networks (ANNs) are universal function approximators, their black box nature (that is, their lack of direct interpretability or expressive power) limits their...
A Meta-Representation for Integrating OR and AI in an Intelligent Decision Support Paradigm (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D., Kozan, Erhan
Operational research (OR) and artificial intelligence (AI) models are primary contributors to the area of intelligent decision support systems (IDSS). Constraint logic programming (CLP) has been used...
A Meta-Representation for Integrating OR and AI in an Intelligent Decision Support Paradigm (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D., Kozan, Erhan
Operational research (OR) and artificial intelligence (AI) models are primary contributors to the area of intelligent decision support systems (IDSS). Constraint logic programming (CLP) has been used...
A Meta-Representation for Integrating OR and AI in an Intelligent Decision Support Paradigm (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D., Kozan, Erhan
Operational research (OR) and artificial intelligence (AI) models are primary contributors to the area of intelligent decision support systems (IDSS). Constraint logic programming (CLP) has been used...
A Meta-Representation for Integrating OR and AI in an Intelligent Decision Support Paradigm (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D., Kozan, Erhan
Operational research (OR) and artificial intelligence (AI) models are primary contributors to the area of intelligent decision support systems (IDSS). Constraint logic programming (CLP) has been used...
C-Net: a method for generating non-deterministic and dynamic multivariate decision trees (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D.
Despite the fact that artificial neural networks (ANNs) are universal function approximators, their black box nature (that is, their lack of direct interpretability or expressive power) limits their...
A Meta-Representation for Integrating OR and AI in an Intelligent Decision Support Paradigm (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D., Kozan, Erhan
Operational research (OR) and artificial intelligence (AI) models are primary contributors to the area of intelligent decision support systems (IDSS). Constraint logic programming (CLP) has been used...
C-Net: a method for generating non-deterministic and dynamic multivariate decision trees (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D.
Despite the fact that artificial neural networks (ANNs) are universal function approximators, their black box nature (that is, their lack of direct interpretability or expressive power) limits their...
A Meta-Representation for Integrating OR and AI in an Intelligent Decision Support Paradigm (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D., Kozan, Erhan
Operational research (OR) and artificial intelligence (AI) models are primary contributors to the area of intelligent decision support systems (IDSS). Constraint logic programming (CLP) has been used...
C-Net: a method for generating non-deterministic and dynamic multivariate decision trees (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D.
Despite the fact that artificial neural networks (ANNs) are universal function approximators, their black box nature (that is, their lack of direct interpretability or expressive power) limits their...
A Meta-Representation for Integrating OR and AI in an Intelligent Decision Support Paradigm (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D., Kozan, Erhan
Operational research (OR) and artificial intelligence (AI) models are primary contributors to the area of intelligent decision support systems (IDSS). Constraint logic programming (CLP) has been used...
C-Net: a method for generating non-deterministic and dynamic multivariate decision trees (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D.
Despite the fact that artificial neural networks (ANNs) are universal function approximators, their black box nature (that is, their lack of direct interpretability or expressive power) limits their...
A monogenous MBO approach to satisfiability (2001)
The marriage in honey–bees optimization (MBO) algorithm was recently proposed and showed good results for combinatorial optimization problems. Contrary to most of the swarm intelligence algorithms...
Simultaneous evolution of architectures and connection weights in anns (2001)
Hussein A. Abbass, Ruhul A. Sarker
Feed-forward Artificial Neural Networks (ANNs) have become popular among researchers and practitioners for modelling complex real–world problems. One of the latest research areas in this field is...
Marriage in Honey Bees Optimization (MBO) is a new swarm intelligence technique inspired by the marriage process of honey bees. It has been shown to be very effective in solving a special group of...
Hussein A. Abbass, Ruhul Sarker, Charles Newton
The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as Multi-objective Optimization Problems (MOPs)) has attracted much attention recently. Being population...
A Meta-Representation for Integrating OR and AI in an Intelligent Decision Support Paradigm (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D., Kozan, Erhan
Operational research (OR) and artificial intelligence (AI) models are primary contributors to the area of intelligent decision support systems (IDSS). Constraint logic programming (CLP) has been used...
C-Net: a method for generating non-deterministic and dynamic multivariate decision trees (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D.
Despite the fact that artificial neural networks (ANNs) are universal function approximators, their black box nature (that is, their lack of direct interpretability or expressive power) limits their...
A Meta-Representation for Integrating OR and AI in an Intelligent Decision Support Paradigm (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D., Kozan, Erhan
Operational research (OR) and artificial intelligence (AI) models are primary contributors to the area of intelligent decision support systems (IDSS). Constraint logic programming (CLP) has been used...
C-Net: a method for generating non-deterministic and dynamic multivariate decision trees (2001)
Abbass, Hussein A., Towsey, Michael W., Finn, Gerard D.
Despite the fact that artificial neural networks (ANNs) are universal function approximators, their black box nature (that is, their lack of direct interpretability or expressive power) limits their...
Bayesian neural network learning for prediction in the Australian dairy industry (1999)
Macrossan, Paula E., Abbass, Hussein A., Mengersen, Kerrie L., Towsey, Michael W., Finn, Gerard
One of the most common problems encountered in agriculture is that of predicting a response variable from covariates of interest. The aim of this paper is to use a Bayesian neural network approach to...
Bayesian neural network learning for prediction in the Australian dairy industry (1999)
Macrossan, Paula E., Abbass, Hussein A., Mengersen, Kerry, Towsey, Michael W., Finn, Gerard
One of the most common problems encountered in agriculture is that of predicting a response variable from covariates of interest. The aim of this paper is to use a Bayesian neural network approach to...
Bayesian neural network learning for prediction in the Australian dairy industry (1999)
Macrossan, Paula E., Abbass, Hussein A., Mengersen, Kerrie L., Towsey, Michael W., Finn, Gerard
One of the most common problems encountered in agriculture is that of predicting a response variable from covariates of interest. The aim of this paper is to use a Bayesian neural network approach to...
Bayesian neural network learning for prediction in the Australian dairy industry (1999)
Macrossan, Paula E., Abbass, Hussein A., Mengersen, Kerrie L., Towsey, Michael W., Finn, Gerard
One of the most common problems encountered in agriculture is that of predicting a response variable from covariates of interest. The aim of this paper is to use a Bayesian neural network approach to...
Bayesian neural network learning for prediction in the Australian dairy industry (1999)
Macrossan, Paula E., Abbass, Hussein A., Mengersen, Kerrie L., Towsey, Michael W., Finn, Gerard
One of the most common problems encountered in agriculture is that of predicting a response variable from covariates of interest. The aim of this paper is to use a Bayesian neural network approach to...
Bayesian neural network learning for prediction in the Australian dairy industry (1999)
Macrossan, Paula E., Abbass, Hussein A., Mengersen, Kerrie L., Towsey, Michael W., Finn, Gerard
One of the most common problems encountered in agriculture is that of predicting a response variable from covariates of interest. The aim of this paper is to use a Bayesian neural network approach to...
Bayesian neural network learning for prediction in the Australian dairy industry (1999)
Macrossan, Paula E., Abbass, Hussein A., Mengersen, Kerrie L., Towsey, Michael W., Finn, Gerard
One of the most common problems encountered in agriculture is that of predicting a response variable from covariates of interest. The aim of this paper is to use a Bayesian neural network approach to...
Bayesian neural network learning for prediction in the Australian dairy industry (1999)
Macrossan, Paula E., Abbass, Hussein A., Mengersen, Kerrie L., Towsey, Michael W., Finn, Gerard
One of the most common problems encountered in agriculture is that of predicting a response variable from covariates of interest. The aim of this paper is to use a Bayesian neural network approach to...
Bayesian neural network learning for prediction in the Australian dairy industry (1999)
Macrossan, Paula E., Abbass, Hussein A., Mengersen, Kerrie L., Towsey, Michael W., Finn, Gerard
One of the most common problems encountered in agriculture is that of predicting a response variable from covariates of interest. The aim of this paper is to use a Bayesian neural network approach to...
Validation and Abstraction (1998)
Minh-ha Nguyen, Robert I. Mckay, Minh Ha Nguyen, Robert I Mckay, Hussein A. Abbass, Hussein A. Abbass
Combining several suitable neural networks can enhance the generalization performance of the group when compared to a single network alone. However it remains a largely open question, how best to...
A MULTI-OBJECTIVE RISK-BASED FRAMEWORK FOR MISSION CAPABILITY PLANNING
LAM T. BUI, MICHAEL BARLOW, HUSSEIN A. ABBASS
In this paper, we propose a risk-based framework for military capability planning. Within this framework, metaheuristic techniques such as Evolutionary Algorithms are used to deal with...