Incorporating several interacting and autonomous components, multi-agent systems can potentially ... more Incorporating several interacting and autonomous components, multi-agent systems can potentially manage the complexity inherent in distributed software systems offering a promising software engineering solution for developing robust and scalable applications. A software infrastructure using multi-agent systems intended to support the distributed design environment by enabling flow of information is proposed. Ontologies are engaged to represent the knowledge of the distributed
PRODUCT LIFE CYCLE DESIGN USING THE DFE WORKBENCH Elena Man1, Juan Enrique Dfez2, Camelia Chira3,... more PRODUCT LIFE CYCLE DESIGN USING THE DFE WORKBENCH Elena Man1, Juan Enrique Dfez2, Camelia Chira3, Thomas Roche4 National University of Ireland, Galway; Galway Mayo Institute of Technology, Ireland 2'3'4 elena. man@ nuigalway. ie, juanenlO@ teleline. es, camelia. chira@ nuigulway. ie thomas. roche@ nuigalway. ie This paper proposes a new design framework for the development of Environmental Superior Products (ESPs) and based on this framework a new DFE methodology and tool called the DFE Workbench is presented. ...
2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence, 2013
ABSTRACT The complex regimes of operation situated between ordered and chaotic behavior are hypot... more ABSTRACT The complex regimes of operation situated between ordered and chaotic behavior are hypothesized to give rise to computational capabilities. Lacking an universal blueprint for the emergence of complexity, a costly search is typically used to find the configurations of distributed artificial systems that can facilitate global computation. In this paper, we address the tedious task of searching for complex cellular automata rules able to lead to a certain global behavior based on local interactions. The discovery of rules exhibiting a high degree of global self-organization is of major importance in the study and understanding of complex systems. A classical heuristic search guided only by a coarse approximation of the ability of a rule to perform in certain conditions will generally not reach beyond an ordered regime of operation. To overcome this limitation, in this paper we incorporate a promising heuristic that rewards increased dynamics with regard to cell state changes in a multiobjective, parallel evolutionary framework. The scope of the multiobjective formulation is to balance the search between ordered and chaotic regimes in order to facilitate the discovery of rules exhibiting complex behaviors. Experimental results confirm that the combined approach represents an efficient way for supporting the emergence of complexity as in all runs we were able to find cellular automata exhibiting a high degree of global self-organization.
Abstract The collaboration process among individuals with heterogeneous skills in a distributed v... more Abstract The collaboration process among individuals with heterogeneous skills in a distributed virtual environment represents a crucial element of the extended enterprise. In order to achieve global optima in design, there is an increasing need for design teams to establish and maintain cooperative work through effective communication, co-location, coordination and collaboration at the knowledge level. Because of the distributed nature of users and information resources involved in the design process, the need for appropriate ...
This paper describes the development of the unified conformational sampling and docking tool call... more This paper describes the development of the unified conformational sampling and docking tool called Sampler for Multiple Protein-Ligand Entities (S4MPLE). The main novelty in S4MPLE is the unified dealing with intra- and intermolecular degrees of freedom (DoF). While classically programs are either designed for folding or docking, S4MPLE transcends this artificial specialization. It supports folding, docking of a flexible ligand into a flexible site and simultaneous docking of several ligands. The trick behind it is the formal assimilation of inter-molecular to intra-molecular DoF associated to putative inter-molecular contact axes. This is implemented within the genetic operators powering a Lamarckian Genetic Algorithm (GA). Further novelty includes differentiable interaction fingerprints to control population diversity, and fitting a simple continuum solvent model and favorable contact bonus terms to the AMBER/GAFF force field. Novel applications-docking of fragment-like compounds...
Abstract. Design activities are becoming an increasingly global, complex, multidisciplinary, info... more Abstract. Design activities are becoming an increasingly global, complex, multidisciplinary, information and knowledge intensive activity. This paper proposes to address the problems associated with communication and knowledge management activities within a distributed design environment by adopting an Ontological-oriented Multi-Agent-based System (MAS) approach to knowledge management within a distributed design environment. This approach will utilize a Multi-Agent System architecture that will interactively assist in the ...
Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation - GECCO '08, 2008
A novel approach to multimodal optimization called Roaming Agent-Based Collaborative Evolutionary... more A novel approach to multimodal optimization called Roaming Agent-Based Collaborative Evolutionary Model (RACE) combining several evolutionary techniques with agent-based modeling is proposed. RACE model aims to detect multiple global and local optima by training a multi-agent system to employ various evolutionary techniques suitable for a specified multimodal optimization problem. Agents can exchange information during the search process enabling a cooperative search of optima between several populations evolving independently. Redundant search by multiple agents is avoided by having them communicate and negotiate about the space region searched. An agent can request and receive from another agent valuable information and genetic material for a better search of a certain region in the environment. Performance of the proposed agent-based collaborative evolutionary model is compared by means of numerical experiments with rival evolutionary techniques.
The prediction of a minimum-energy protein structure from its amino-acid sequence represents one ... more The prediction of a minimum-energy protein structure from its amino-acid sequence represents one of the most important and challenging problems in computational biology. A new evolutionary model based on hill-climbing genetic operators is proposed to address the hydrophobic - polar model of the protein folding problem. The introduced model ensures an efficient exploration of the search space by implementing a
Systems composed of several interacting autonomous agents have a huge potential to efficiently ad... more Systems composed of several interacting autonomous agents have a huge potential to efficiently address complex real-world problems. A new Learning Sensitive Agent System (LSAS) is proposed to address combinatorial optimization problems. Agents communicate by directly exchanging information and knowledge about the environment. Furthermore, agents of the proposed model are endowed with stigmergic behavior and are able to indirectly communicate by producing and being influenced by pheromone trails. Each stigmergic agent has a certain level of sensitivity to the pheromone allowing various types of reactions to a changing environment. For better search diversification and intensification, agents can learn to modify their sensitivity level according to environment characteristics and previous experience. The proposed LSAS model is tested for solving various instances of the Asymmetric Traveling Salesman Problem. Numerical experiments indicate the robustn ess and potential of the new metaheuristic. C. Chira et al.: Cooperative Learning Sensitive Agent System for Combinatorial Optimization, Studies in Computational Intelligence (SCI) 129, 347-355 (2008) www.springerlink.com c Springer-Verlag Berlin Heidelberg 2008 348 C. Chira et al.
Abstract. The evolution of the human society raises more and more difficult endeavors. For some o... more Abstract. The evolution of the human society raises more and more difficult endeavors. For some of the real-life problems, the computing time-restriction enhances their complexity. The Matrix Bandwidth Minimization Problem (MBMP) seeks for a simultaneous permutation of the rows and the columns of a square matrix in order to keep its nonzero entries close to the main diagonal. The MBMP is a highly investigated NP-complete problem, as it has broad applications in industry, logistics, artificial intelligence or information recovery. This paper ...
A metaheuristic called Sensitive Ant Model (SAM) for solving combinatorial optimization problems ... more A metaheuristic called Sensitive Ant Model (SAM) for solving combinatorial optimization problems is developed. The proposed model is based on the Ant Colony System (ACS) algorithm in which agents cooperate indirectly using pheromone trails. SAM improves and extends the ACS approach by endowing each agent of the model with properties that induce heterogeneity. Different pheromone sensitivity levels are used for agents in the population. Highly-sensitive agents are essentially influenced in the decision making process by ...
A multi-agent approach to solving dynamic Traveling Salesman Problem (TSP) is presented. In the d... more A multi-agent approach to solving dynamic Traveling Salesman Problem (TSP) is presented. In the dynamic version of TSP cities can be dynamically added or removed. Proposed multi-agent approach is based on the Sensitive Stigmergic Agent System model refined with new type of messages between agents. The agents send messages every time a change occurs, for instance, when an agent observes
Abstract: Enterprise models of engineering design involve multiple distributed design teams with ... more Abstract: Enterprise models of engineering design involve multiple distributed design teams with heterogeneous skills cooperating together in order to achieve global optima in design. The success of this distributed design organization depends on critical factors such as the efficient management of the design related information circulated in the distributed environment and the support for the necessary cooperation processes among participants dispersed across the enterprise. This paper proposes a multi-agent design information ...
ABSTRACT Gene expression microarray data provides simultaneous activity measurement of thousands ... more ABSTRACT Gene expression microarray data provides simultaneous activity measurement of thousands of features facilitating a potential effective and reliable cancer diagnosis. An important and challenging task in microarray analysis refers to selecting the most relevant and significant genes for data cancer classification. A random subspace ensemble based method is proposed to address feature selection in gene expression cancer diagnosis. The introduced Diverse Accurate Feature Selection method relies on multiple individual classifiers built based on random feature subspaces. Each feature is assigned a score computed based on the pairwise diversity among individual classifiers and the ratio between individual and ensemble accuracies. This triggers the creation of a ranked list of features for which a final classifier is applied with an increased performance using minimum possible number of genes. Experimental results focus on the problem of gene expression cancer diagnosis based on microarray datasets publicly available. Numerical results show that the proposed method is competitive with related models from literature.
ABSTRACT Permutation-based encoding is used by many evolutionary algorithms dealing with combinat... more ABSTRACT Permutation-based encoding is used by many evolutionary algorithms dealing with combinatorial optimization problems. An important aspect of the evolutionary search process refers to the recombination process of existing individuals in order to generate new potentially better fit offspring leading to more promising areas of the search space. In this paper, we describe and analyze the best-order recombination operator for permutation-based encoding. The proposed operator uses genetic information from the two parents and from the best individual obtained up to the current generation. These sources of information are integrated to determine the best order of values in the new permutation. In order to evaluate the performance of best-order crossover, we address three well-known \(\mathcal {NP}\) -hard optimization problems i.e. Travelling Salesman Problem, Vehicle Routing Problem and Resource-Constrained Project Scheduling Problem. For each of these problems, a set of benchmark instances is considered in a comparative analysis of the proposed operator with eight other crossover schemes designed for permutation representation. All crossover operators are integrated in the same standard evolutionary framework and using the same parameter setting to allow a comparison focused on the recombination process. Numerical results emphasize a good performance of the proposed crossover scheme which is able to lead to overall better quality solutions.
Incorporating several interacting and autonomous components, multi-agent systems can potentially ... more Incorporating several interacting and autonomous components, multi-agent systems can potentially manage the complexity inherent in distributed software systems offering a promising software engineering solution for developing robust and scalable applications. A software infrastructure using multi-agent systems intended to support the distributed design environment by enabling flow of information is proposed. Ontologies are engaged to represent the knowledge of the distributed
PRODUCT LIFE CYCLE DESIGN USING THE DFE WORKBENCH Elena Man1, Juan Enrique Dfez2, Camelia Chira3,... more PRODUCT LIFE CYCLE DESIGN USING THE DFE WORKBENCH Elena Man1, Juan Enrique Dfez2, Camelia Chira3, Thomas Roche4 National University of Ireland, Galway; Galway Mayo Institute of Technology, Ireland 2'3'4 elena. man@ nuigalway. ie, juanenlO@ teleline. es, camelia. chira@ nuigulway. ie thomas. roche@ nuigalway. ie This paper proposes a new design framework for the development of Environmental Superior Products (ESPs) and based on this framework a new DFE methodology and tool called the DFE Workbench is presented. ...
2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence, 2013
ABSTRACT The complex regimes of operation situated between ordered and chaotic behavior are hypot... more ABSTRACT The complex regimes of operation situated between ordered and chaotic behavior are hypothesized to give rise to computational capabilities. Lacking an universal blueprint for the emergence of complexity, a costly search is typically used to find the configurations of distributed artificial systems that can facilitate global computation. In this paper, we address the tedious task of searching for complex cellular automata rules able to lead to a certain global behavior based on local interactions. The discovery of rules exhibiting a high degree of global self-organization is of major importance in the study and understanding of complex systems. A classical heuristic search guided only by a coarse approximation of the ability of a rule to perform in certain conditions will generally not reach beyond an ordered regime of operation. To overcome this limitation, in this paper we incorporate a promising heuristic that rewards increased dynamics with regard to cell state changes in a multiobjective, parallel evolutionary framework. The scope of the multiobjective formulation is to balance the search between ordered and chaotic regimes in order to facilitate the discovery of rules exhibiting complex behaviors. Experimental results confirm that the combined approach represents an efficient way for supporting the emergence of complexity as in all runs we were able to find cellular automata exhibiting a high degree of global self-organization.
Abstract The collaboration process among individuals with heterogeneous skills in a distributed v... more Abstract The collaboration process among individuals with heterogeneous skills in a distributed virtual environment represents a crucial element of the extended enterprise. In order to achieve global optima in design, there is an increasing need for design teams to establish and maintain cooperative work through effective communication, co-location, coordination and collaboration at the knowledge level. Because of the distributed nature of users and information resources involved in the design process, the need for appropriate ...
This paper describes the development of the unified conformational sampling and docking tool call... more This paper describes the development of the unified conformational sampling and docking tool called Sampler for Multiple Protein-Ligand Entities (S4MPLE). The main novelty in S4MPLE is the unified dealing with intra- and intermolecular degrees of freedom (DoF). While classically programs are either designed for folding or docking, S4MPLE transcends this artificial specialization. It supports folding, docking of a flexible ligand into a flexible site and simultaneous docking of several ligands. The trick behind it is the formal assimilation of inter-molecular to intra-molecular DoF associated to putative inter-molecular contact axes. This is implemented within the genetic operators powering a Lamarckian Genetic Algorithm (GA). Further novelty includes differentiable interaction fingerprints to control population diversity, and fitting a simple continuum solvent model and favorable contact bonus terms to the AMBER/GAFF force field. Novel applications-docking of fragment-like compounds...
Abstract. Design activities are becoming an increasingly global, complex, multidisciplinary, info... more Abstract. Design activities are becoming an increasingly global, complex, multidisciplinary, information and knowledge intensive activity. This paper proposes to address the problems associated with communication and knowledge management activities within a distributed design environment by adopting an Ontological-oriented Multi-Agent-based System (MAS) approach to knowledge management within a distributed design environment. This approach will utilize a Multi-Agent System architecture that will interactively assist in the ...
Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation - GECCO '08, 2008
A novel approach to multimodal optimization called Roaming Agent-Based Collaborative Evolutionary... more A novel approach to multimodal optimization called Roaming Agent-Based Collaborative Evolutionary Model (RACE) combining several evolutionary techniques with agent-based modeling is proposed. RACE model aims to detect multiple global and local optima by training a multi-agent system to employ various evolutionary techniques suitable for a specified multimodal optimization problem. Agents can exchange information during the search process enabling a cooperative search of optima between several populations evolving independently. Redundant search by multiple agents is avoided by having them communicate and negotiate about the space region searched. An agent can request and receive from another agent valuable information and genetic material for a better search of a certain region in the environment. Performance of the proposed agent-based collaborative evolutionary model is compared by means of numerical experiments with rival evolutionary techniques.
The prediction of a minimum-energy protein structure from its amino-acid sequence represents one ... more The prediction of a minimum-energy protein structure from its amino-acid sequence represents one of the most important and challenging problems in computational biology. A new evolutionary model based on hill-climbing genetic operators is proposed to address the hydrophobic - polar model of the protein folding problem. The introduced model ensures an efficient exploration of the search space by implementing a
Systems composed of several interacting autonomous agents have a huge potential to efficiently ad... more Systems composed of several interacting autonomous agents have a huge potential to efficiently address complex real-world problems. A new Learning Sensitive Agent System (LSAS) is proposed to address combinatorial optimization problems. Agents communicate by directly exchanging information and knowledge about the environment. Furthermore, agents of the proposed model are endowed with stigmergic behavior and are able to indirectly communicate by producing and being influenced by pheromone trails. Each stigmergic agent has a certain level of sensitivity to the pheromone allowing various types of reactions to a changing environment. For better search diversification and intensification, agents can learn to modify their sensitivity level according to environment characteristics and previous experience. The proposed LSAS model is tested for solving various instances of the Asymmetric Traveling Salesman Problem. Numerical experiments indicate the robustn ess and potential of the new metaheuristic. C. Chira et al.: Cooperative Learning Sensitive Agent System for Combinatorial Optimization, Studies in Computational Intelligence (SCI) 129, 347-355 (2008) www.springerlink.com c Springer-Verlag Berlin Heidelberg 2008 348 C. Chira et al.
Abstract. The evolution of the human society raises more and more difficult endeavors. For some o... more Abstract. The evolution of the human society raises more and more difficult endeavors. For some of the real-life problems, the computing time-restriction enhances their complexity. The Matrix Bandwidth Minimization Problem (MBMP) seeks for a simultaneous permutation of the rows and the columns of a square matrix in order to keep its nonzero entries close to the main diagonal. The MBMP is a highly investigated NP-complete problem, as it has broad applications in industry, logistics, artificial intelligence or information recovery. This paper ...
A metaheuristic called Sensitive Ant Model (SAM) for solving combinatorial optimization problems ... more A metaheuristic called Sensitive Ant Model (SAM) for solving combinatorial optimization problems is developed. The proposed model is based on the Ant Colony System (ACS) algorithm in which agents cooperate indirectly using pheromone trails. SAM improves and extends the ACS approach by endowing each agent of the model with properties that induce heterogeneity. Different pheromone sensitivity levels are used for agents in the population. Highly-sensitive agents are essentially influenced in the decision making process by ...
A multi-agent approach to solving dynamic Traveling Salesman Problem (TSP) is presented. In the d... more A multi-agent approach to solving dynamic Traveling Salesman Problem (TSP) is presented. In the dynamic version of TSP cities can be dynamically added or removed. Proposed multi-agent approach is based on the Sensitive Stigmergic Agent System model refined with new type of messages between agents. The agents send messages every time a change occurs, for instance, when an agent observes
Abstract: Enterprise models of engineering design involve multiple distributed design teams with ... more Abstract: Enterprise models of engineering design involve multiple distributed design teams with heterogeneous skills cooperating together in order to achieve global optima in design. The success of this distributed design organization depends on critical factors such as the efficient management of the design related information circulated in the distributed environment and the support for the necessary cooperation processes among participants dispersed across the enterprise. This paper proposes a multi-agent design information ...
ABSTRACT Gene expression microarray data provides simultaneous activity measurement of thousands ... more ABSTRACT Gene expression microarray data provides simultaneous activity measurement of thousands of features facilitating a potential effective and reliable cancer diagnosis. An important and challenging task in microarray analysis refers to selecting the most relevant and significant genes for data cancer classification. A random subspace ensemble based method is proposed to address feature selection in gene expression cancer diagnosis. The introduced Diverse Accurate Feature Selection method relies on multiple individual classifiers built based on random feature subspaces. Each feature is assigned a score computed based on the pairwise diversity among individual classifiers and the ratio between individual and ensemble accuracies. This triggers the creation of a ranked list of features for which a final classifier is applied with an increased performance using minimum possible number of genes. Experimental results focus on the problem of gene expression cancer diagnosis based on microarray datasets publicly available. Numerical results show that the proposed method is competitive with related models from literature.
ABSTRACT Permutation-based encoding is used by many evolutionary algorithms dealing with combinat... more ABSTRACT Permutation-based encoding is used by many evolutionary algorithms dealing with combinatorial optimization problems. An important aspect of the evolutionary search process refers to the recombination process of existing individuals in order to generate new potentially better fit offspring leading to more promising areas of the search space. In this paper, we describe and analyze the best-order recombination operator for permutation-based encoding. The proposed operator uses genetic information from the two parents and from the best individual obtained up to the current generation. These sources of information are integrated to determine the best order of values in the new permutation. In order to evaluate the performance of best-order crossover, we address three well-known \(\mathcal {NP}\) -hard optimization problems i.e. Travelling Salesman Problem, Vehicle Routing Problem and Resource-Constrained Project Scheduling Problem. For each of these problems, a set of benchmark instances is considered in a comparative analysis of the proposed operator with eight other crossover schemes designed for permutation representation. All crossover operators are integrated in the same standard evolutionary framework and using the same parameter setting to allow a comparison focused on the recombination process. Numerical results emphasize a good performance of the proposed crossover scheme which is able to lead to overall better quality solutions.
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Papers by Camelia Chira