German Terrazas | University of Nottingham (original) (raw)

Papers by German Terrazas

Journal of Manufacturing and Materials Processing

The new generation of ICT solutions applied to the monitoring, adaptation, simulation and optimis... more The new generation of ICT solutions applied to the monitoring, adaptation, simulation and optimisation of factories are key enabling technologies for a new level of manufacturing capability and adaptability in the context of Industry 4.0. Given the advances in sensor technologies, factories, as well as machine tools can now be sensorised, and the vast amount of data generated can be exploited by intelligent information processing techniques such as machine learning. This paper presents an online tool wear classification system built in terms of a monitoring infrastructure, dedicated to perform dry milling on steel while capturing force signals, and a computing architecture, assembled for the assessment of the flank wear based on deep learning. In particular, this approach demonstrates that a big data analytics method for classification applied to large volumes of continuously-acquired force signals generated at high speed during milling responds sufficiently well when used as an ind...

Nature inspired computing is nowadays part of a global emerging paradigm. Diverse biological proc... more Nature inspired computing is nowadays part of a global emerging paradigm. Diverse biological processes, natural evolution and other complex cooperative systems in nature have always been a fruitful source of inspiration for computer science leading to the development of highly effective problem solving algorithms and computing strategies. Well known examples include evolutionary algorithms, ant colony optimization, artificial immune systems, particle swarm optimization, membrane computing and artificial bee colonies.

In a previous work we have reported on the evolutionary design optimisation of self-assembling Wa... more In a previous work we have reported on the evolutionary design optimisation of self-assembling Wang tiles. Apart from the achieved findings [11], nothing has been yet said about the effectiveness by which individuals were evaluated. In particular when the mapping from genotype to phenotype and from this to fitness is an intricate relationship. In this paper we aim to report whether our genetic algorithm, using morphological image analyses as fitness function, is an effective methodology. Thus, we present here fitness distance correlation to measure how effectively the fitness of an individual correlates to its genotypic distance to a known optimum when the genotype-phenotype-fitness mapping is a complex, stochastic and non-linear relationship.

Porphyrins are molecular units with fourfold symmetry and suitable for solid substrate deposition... more Porphyrins are molecular units with fourfold symmetry and suitable for solid substrate deposition. The chemical structure of a porphyrin molecule reveals four structural units which can be synthesised with different substituent functional groups. The adequate selection of functional groups plays a central role in defining the correct intermolecular bindings that lead to a precisely tuned spatial self-assembled pattern. In this paper we explore the state-space of self-assembled programmable patterns. This is done by modelling the porphyrins molecular units using a kinetic Monte Carlo approach. Furthermore we analyse our simulations by both deriving discrete computational automata and in terms of algorithmic information content.

Self-assembly and self-organisation are natural construction processes where the spontaneous form... more Self-assembly and self-organisation are natural construction processes where the spontaneous formation of aggregates emerges throughout the progressive interplay of local interactions among its constituents. Made upon cooperative self-reliant components, self-assembly and self-organising systems are seen as distributed, not necessarily synchronous, autopoietic mechanisms for the bottom-up fabrication of supra-structures. The systematic understanding of how nature endows these autonomous components with sufficient ''intelligence'' to combine themselves to form useful aggregates brings challenging questions to science, answers to which have many potential applications in matters of life and technological advances. It is for this reason that the investigation to be presented along this thesis focuses on the automated design of self-assembly and self-organising systems by means of artificial evolution. Towards this goal, this dissertation embodies research on evolutionar...

Studies in Computational Intelligence, 2011

In a previous work we have reported on the evolutionary design optimisation of self-assembling Wa... more In a previous work we have reported on the evolutionary design optimisation of self-assembling Wang tiles. Apart from the achieved findings [11], nothing has been yet said about the effectiveness by which individuals were evaluated. In particular when the mapping from genotype to phenotype and from this to fitness is an intricate relationship. In this paper we aim to report whether our genetic algorithm, using morphological image analyses as fitness function, is an effective methodology. Thus, we present here fitness distance correlation to measure how effectively the fitness of an individual correlates to its genotypic distance to a known optimum when the genotype-phenotype-fitness mapping is a complex, stochastic and non-linear relationship.

Porphyrins are molecular units with fourfold symmetry and suitable for solid substrate deposition... more Porphyrins are molecular units with fourfold symmetry and suitable for solid substrate deposition. The chemical structure of a porphyrin molecule reveals four structural units which can be synthesised with different substituent functional groups. The adequate selection of functional groups plays a central role in defining the correct intermolecular bindings that lead to a precisely tuned spatial self-assembled pattern. In this paper we explore the state-space of self-assembled programmable patterns. This is done by modelling the porphyrins molecular units using a kinetic Monte Carlo approach. Furthermore we analyse our simulations by both deriving discrete computational automata and in terms of algorithmic information content.

Memetic Computing, 2013

ABSTRACT In a previous work we have reported on the evolutionary design optimisation of self-asse... more ABSTRACT In a previous work we have reported on the evolutionary design optimisation of self-assembling Wang tiles capable of arranging themselves together into a target structure. Apart from the significant findings on how self-assembly is achieved, nothing has been yet said about the efficiency by which individuals were evolved. Specially in light that the mapping from genotype to phenotype and from this to fitness is clearly a complex, stochastic and non-linear relationship. One of the most common procedures would suggest running many experiments for different configurations followed by a fitness comparison, which is not only time-consuming but also inaccurate for such intricate mappings. In this paper we aim to report on a complementary dual assessment protocol to analyse whether our genetic algorithm, using morphological image analyses as fitness function, is an effective methodology. Thus, we present here fitness distance correlation to measure how effectively the fitness of an individual correlates to its genotypic distance to a known optimum, and introduce clustering as a mechanism to verify how the objective function can effectively differentiate between dissimilar phenotypes and classify similar ones for the purpose of selection.

The current research trends on hyper-heuristics design have sprung up in two different flavours: ... more The current research trends on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics. In the latter, the goal is to develop a problem-domain independent strategy to automatically generate a good performing heuristic for specific problems, that is, the input to the algorithm are problems and the output are problem-tailored heuristics. This can be done, for example, by automatically selecting and combining different low-level heuristics into a problem specific and effective strategy. Thus, hyper-heuristics raise the level of generality on automated problem solving by attempting to select and/or generate tailored heuristics for the problem in hand. Some approaches like genetic programming have been proposed for this. In this paper, we report on an alternative methodology that sheds light on simple methodologies that efficiently cooperate by means of local interactions. These entities are seen as building blocks, the combination of which is employed for the automated manufacture of good performing heuristic search strategies. We present proof-of-concept results of applying this methodology to instances of the well-known symmetric TSP. The goal here is to demonstrate feasibility rather than compete with state of the art TSP solvers. This TSP is chosen only because it is an easy to state and well known problem.

Lecture Notes in Computer Science, 2005

Quorum Sensing" has been identified as one of the most consequential microbiology discoveries of ... more Quorum Sensing" has been identified as one of the most consequential microbiology discoveries of the last 10 years. Using Quorum Sensing bacterial colonies synchronize gene expression and phenotype change allowing them, among other things, to protect their niche, coordinate host invasion and bio-film formation. In this contribution we briefly describe the elementary microbiology background and present a P-systems based model for Quorum Sensing which includes environmental rules and a topological representation.

Bulletin of The European Association for Theoretical Computer Science, 2005

Quorum Sensing" has been identified as one of the most consequential microbiology discoverie... more Quorum Sensing" has been identified as one of the most consequential microbiology discoveries of the last 10 years. Using Quorum Sensing bac- terial colonies synchronize gene expression and phenotype change allowing them, among other things, to protect their niche, coordinate host invasion and bio-film formation. In this contribution we briefly describe the elemen- tary microbiology background and comment on some

Self-assembly is a phenomenon observed in nature at all scales where autonomous entities build co... more Self-assembly is a phenomenon observed in nature at all scales where autonomous entities build complex structures, without external influences nor centralised master plan. Modelling such entities and programming correct interactions among them is crucial for controlling the manufacture of desired complex structures at the molecular and supramolecular scale. This work focuses on a programmability model for non DNA-based molecules and complex behaviour analysis of their self-assembled conformations. In particular, we look into modelling, programming and simulation of porphyrin molecules self-assembly and apply Kolgomorov complexity-based techniques to classify and assess simulation results in terms of information content. The analysis focuses on phase transition, clustering, variability and parameter discovery which as a whole pave the way to the notion of complex systems programmability.

Artificial life, Jan 26, 2015

In the past decades many definitions of complexity have been proposed. Most of these definitions ... more In the past decades many definitions of complexity have been proposed. Most of these definitions are based either on Shannon's information theory or on Kolmogorov complexity; these two are often compared, but very few studies integrate the two ideas. In this article we introduce a new measure of complexity that builds on both of these theories. As a demonstration of the concept, the technique is applied to elementary cellular automata and simulations of the self-organization of porphyrin molecules.

In this chapter we explore various facets of the interplay between natural computing and self-ass... more In this chapter we explore various facets of the interplay between natural computing and self-assembly as they pertain to automated self-assembling programming. In particular we focus on two complementary research issues, namely, the automated control and programming of model systems that self-assemble into specific configurations and, on the other hand, the use of self-assembling metaphors and model systems to implement

In the last decade and especially after Adleman's experiment [1] a number of computational paradi... more In the last decade and especially after Adleman's experiment [1] a number of computational paradigms, inspired or gleaned from biochemical phenomena, are becoming of growing interest building a wealth of models, called generically Molecular Computing. New advances in, on the one hand, molecular and theoretical biology, and on the other hand, mathematical and computational sciences promise to make it possible in the near future to have accurate systemic models of complex biological phenomena. Recent advances in cellular Biology led to new models, hierarchically organised, defining a new emergent research area called Cellular Computing. P-systems represent a class of distributed and parallel computing devices of a biological type that was introduced in [14] which are included in the wider field of cellular computing. Several variants of this model have been investigated and the literature on the subject is now rapidly growing. The main results in this area show that P-systems are a very powerful and efficient computational model , , . There are variants that might be classified according to different criteria. They may be regarded as language generators or acceptors, working with strings or multisets, developing synchronous or asynchronous computation. Two main classes of P-systems can be identified in the area of membrane computing [15]: cell-like P-systems and tissue-like P-systems. The former type is inspired by the internal organization of living cells with different compartments and membranes hierarchically arranged; formally this structure is associated with a tree. Tissue P-systems have been motivated by the structure and behaviour of multicellular organisms where they form a multitude of different tissues performing various functions [2]; the structure of the system is instead represented as a graph where nodes are associated with the cells which are allowed to communicate alongside the edges of the graph.

Many aspects of Nature, Biology or even from Society have become part of the techniques and algor... more Many aspects of Nature, Biology or even from Society have become part of the techniques and algorithms used in computer science or they have been used to enhance or hybridize several techniques through the inclusion of advanced evolution, cooperation or biologically based additions. The previous NICSO workshops were held in Granada, Spain, 2006, Acireale, Italy, 2007, and in Tenerife, Spain, 2008. As in the previous editions, NICSO 2010, held in Granada, Spain, was conceived as a forum for the latest ideas and the state of the ...

Self-assembly is a distributed, asynchronous mechanism that is pervasive across natural systems w... more Self-assembly is a distributed, asynchronous mechanism that is pervasive across natural systems where hierarchical complex structures are built from the bottom-up. The lack of a centralised master plan, no external intervention, and preprogrammed interactions among entities are within its most relevant and technologically appealing properties. This paper tackles the self-assembly Wang tiles designability problem by means of artificial evolution. This research is centred in the use of tiles that are extended with rotation and probabilistic motion, and an evolutionary algorithm using the Morphological Image Analyses method as a fitness function. The obtained results support this approach as a successful engineering mechanism for the computer-aided design of self-assembled patterns.

Cellular automata (CA) are an important modelling paradigm in the natural sciences and an extreme... more Cellular automata (CA) are an important modelling paradigm in the natural sciences and an extremely useful approach in the study of complex systems. Homogeneity, massive parallelism, local cellular interactions and both synchronous and asynchronous models of rule execution are some of their most prominent features, allowing scientists to model and understand a variety of phenomena in, to name but a few, the physical, chemical, biological, social and information sciences. An ubiquitous problem related with the study of complex systems by means of CA is that of parameter identification. In some cases, analytical methods are available but in many others, due to the bottom-up complexity of the underlying processes, the best route for CA identification is through design optimization by means of a metaheuristic, such as an evolutionary algorithm. In this work we report on a systematic methodology we have developed to control the spatio-temporal behavior of a CA in order to obtain a 'designoid' target pattern. Four independent CA-based complex systems were used to assess our proposal which combines clustering, fitness distance correlation and evolutionary algorithms.

Electronic Proceedings in Theoretical Computer Science, 2010

The current investigations on hyper-heuristics design have sprung up in two different flavours: h... more The current investigations on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics. In the latter, the goal is to develop a problem-domain independent strategy to automatically generate a good performing heuristic for the problem at hand. This can be done, for example, by automatically selecting and combining different low-level heuristics into a problem specific and effective strategy. Hyper-heuristics raise the level of generality on automated problem solving by attempting to select and/or generate tailored heuristics for the problem at hand. Some approaches like genetic programming have been proposed for this. In this paper, we explore an elegant nature-inspired alternative based on self-assembly construction processes, in which structures emerge out of local interactions between autonomous components. This idea arises from previous works in which computational models of self-assembly were subject to evolutionary design in order to perform the automatic construction of user-defined structures. Then, the aim of this paper is to present a novel methodology for the automated design of heuristics by means of self-assembly.

Journal of Manufacturing and Materials Processing

The new generation of ICT solutions applied to the monitoring, adaptation, simulation and optimis... more The new generation of ICT solutions applied to the monitoring, adaptation, simulation and optimisation of factories are key enabling technologies for a new level of manufacturing capability and adaptability in the context of Industry 4.0. Given the advances in sensor technologies, factories, as well as machine tools can now be sensorised, and the vast amount of data generated can be exploited by intelligent information processing techniques such as machine learning. This paper presents an online tool wear classification system built in terms of a monitoring infrastructure, dedicated to perform dry milling on steel while capturing force signals, and a computing architecture, assembled for the assessment of the flank wear based on deep learning. In particular, this approach demonstrates that a big data analytics method for classification applied to large volumes of continuously-acquired force signals generated at high speed during milling responds sufficiently well when used as an ind...

Nature inspired computing is nowadays part of a global emerging paradigm. Diverse biological proc... more Nature inspired computing is nowadays part of a global emerging paradigm. Diverse biological processes, natural evolution and other complex cooperative systems in nature have always been a fruitful source of inspiration for computer science leading to the development of highly effective problem solving algorithms and computing strategies. Well known examples include evolutionary algorithms, ant colony optimization, artificial immune systems, particle swarm optimization, membrane computing and artificial bee colonies.

In a previous work we have reported on the evolutionary design optimisation of self-assembling Wa... more In a previous work we have reported on the evolutionary design optimisation of self-assembling Wang tiles. Apart from the achieved findings [11], nothing has been yet said about the effectiveness by which individuals were evaluated. In particular when the mapping from genotype to phenotype and from this to fitness is an intricate relationship. In this paper we aim to report whether our genetic algorithm, using morphological image analyses as fitness function, is an effective methodology. Thus, we present here fitness distance correlation to measure how effectively the fitness of an individual correlates to its genotypic distance to a known optimum when the genotype-phenotype-fitness mapping is a complex, stochastic and non-linear relationship.

Porphyrins are molecular units with fourfold symmetry and suitable for solid substrate deposition... more Porphyrins are molecular units with fourfold symmetry and suitable for solid substrate deposition. The chemical structure of a porphyrin molecule reveals four structural units which can be synthesised with different substituent functional groups. The adequate selection of functional groups plays a central role in defining the correct intermolecular bindings that lead to a precisely tuned spatial self-assembled pattern. In this paper we explore the state-space of self-assembled programmable patterns. This is done by modelling the porphyrins molecular units using a kinetic Monte Carlo approach. Furthermore we analyse our simulations by both deriving discrete computational automata and in terms of algorithmic information content.

Self-assembly and self-organisation are natural construction processes where the spontaneous form... more Self-assembly and self-organisation are natural construction processes where the spontaneous formation of aggregates emerges throughout the progressive interplay of local interactions among its constituents. Made upon cooperative self-reliant components, self-assembly and self-organising systems are seen as distributed, not necessarily synchronous, autopoietic mechanisms for the bottom-up fabrication of supra-structures. The systematic understanding of how nature endows these autonomous components with sufficient ''intelligence'' to combine themselves to form useful aggregates brings challenging questions to science, answers to which have many potential applications in matters of life and technological advances. It is for this reason that the investigation to be presented along this thesis focuses on the automated design of self-assembly and self-organising systems by means of artificial evolution. Towards this goal, this dissertation embodies research on evolutionar...

Studies in Computational Intelligence, 2011

In a previous work we have reported on the evolutionary design optimisation of self-assembling Wa... more In a previous work we have reported on the evolutionary design optimisation of self-assembling Wang tiles. Apart from the achieved findings [11], nothing has been yet said about the effectiveness by which individuals were evaluated. In particular when the mapping from genotype to phenotype and from this to fitness is an intricate relationship. In this paper we aim to report whether our genetic algorithm, using morphological image analyses as fitness function, is an effective methodology. Thus, we present here fitness distance correlation to measure how effectively the fitness of an individual correlates to its genotypic distance to a known optimum when the genotype-phenotype-fitness mapping is a complex, stochastic and non-linear relationship.

Porphyrins are molecular units with fourfold symmetry and suitable for solid substrate deposition... more Porphyrins are molecular units with fourfold symmetry and suitable for solid substrate deposition. The chemical structure of a porphyrin molecule reveals four structural units which can be synthesised with different substituent functional groups. The adequate selection of functional groups plays a central role in defining the correct intermolecular bindings that lead to a precisely tuned spatial self-assembled pattern. In this paper we explore the state-space of self-assembled programmable patterns. This is done by modelling the porphyrins molecular units using a kinetic Monte Carlo approach. Furthermore we analyse our simulations by both deriving discrete computational automata and in terms of algorithmic information content.

Memetic Computing, 2013

ABSTRACT In a previous work we have reported on the evolutionary design optimisation of self-asse... more ABSTRACT In a previous work we have reported on the evolutionary design optimisation of self-assembling Wang tiles capable of arranging themselves together into a target structure. Apart from the significant findings on how self-assembly is achieved, nothing has been yet said about the efficiency by which individuals were evolved. Specially in light that the mapping from genotype to phenotype and from this to fitness is clearly a complex, stochastic and non-linear relationship. One of the most common procedures would suggest running many experiments for different configurations followed by a fitness comparison, which is not only time-consuming but also inaccurate for such intricate mappings. In this paper we aim to report on a complementary dual assessment protocol to analyse whether our genetic algorithm, using morphological image analyses as fitness function, is an effective methodology. Thus, we present here fitness distance correlation to measure how effectively the fitness of an individual correlates to its genotypic distance to a known optimum, and introduce clustering as a mechanism to verify how the objective function can effectively differentiate between dissimilar phenotypes and classify similar ones for the purpose of selection.

The current research trends on hyper-heuristics design have sprung up in two different flavours: ... more The current research trends on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics. In the latter, the goal is to develop a problem-domain independent strategy to automatically generate a good performing heuristic for specific problems, that is, the input to the algorithm are problems and the output are problem-tailored heuristics. This can be done, for example, by automatically selecting and combining different low-level heuristics into a problem specific and effective strategy. Thus, hyper-heuristics raise the level of generality on automated problem solving by attempting to select and/or generate tailored heuristics for the problem in hand. Some approaches like genetic programming have been proposed for this. In this paper, we report on an alternative methodology that sheds light on simple methodologies that efficiently cooperate by means of local interactions. These entities are seen as building blocks, the combination of which is employed for the automated manufacture of good performing heuristic search strategies. We present proof-of-concept results of applying this methodology to instances of the well-known symmetric TSP. The goal here is to demonstrate feasibility rather than compete with state of the art TSP solvers. This TSP is chosen only because it is an easy to state and well known problem.

Lecture Notes in Computer Science, 2005

Quorum Sensing" has been identified as one of the most consequential microbiology discoveries of ... more Quorum Sensing" has been identified as one of the most consequential microbiology discoveries of the last 10 years. Using Quorum Sensing bacterial colonies synchronize gene expression and phenotype change allowing them, among other things, to protect their niche, coordinate host invasion and bio-film formation. In this contribution we briefly describe the elementary microbiology background and present a P-systems based model for Quorum Sensing which includes environmental rules and a topological representation.

Bulletin of The European Association for Theoretical Computer Science, 2005

Quorum Sensing" has been identified as one of the most consequential microbiology discoverie... more Quorum Sensing" has been identified as one of the most consequential microbiology discoveries of the last 10 years. Using Quorum Sensing bac- terial colonies synchronize gene expression and phenotype change allowing them, among other things, to protect their niche, coordinate host invasion and bio-film formation. In this contribution we briefly describe the elemen- tary microbiology background and comment on some

Self-assembly is a phenomenon observed in nature at all scales where autonomous entities build co... more Self-assembly is a phenomenon observed in nature at all scales where autonomous entities build complex structures, without external influences nor centralised master plan. Modelling such entities and programming correct interactions among them is crucial for controlling the manufacture of desired complex structures at the molecular and supramolecular scale. This work focuses on a programmability model for non DNA-based molecules and complex behaviour analysis of their self-assembled conformations. In particular, we look into modelling, programming and simulation of porphyrin molecules self-assembly and apply Kolgomorov complexity-based techniques to classify and assess simulation results in terms of information content. The analysis focuses on phase transition, clustering, variability and parameter discovery which as a whole pave the way to the notion of complex systems programmability.

Artificial life, Jan 26, 2015

In the past decades many definitions of complexity have been proposed. Most of these definitions ... more In the past decades many definitions of complexity have been proposed. Most of these definitions are based either on Shannon's information theory or on Kolmogorov complexity; these two are often compared, but very few studies integrate the two ideas. In this article we introduce a new measure of complexity that builds on both of these theories. As a demonstration of the concept, the technique is applied to elementary cellular automata and simulations of the self-organization of porphyrin molecules.

In this chapter we explore various facets of the interplay between natural computing and self-ass... more In this chapter we explore various facets of the interplay between natural computing and self-assembly as they pertain to automated self-assembling programming. In particular we focus on two complementary research issues, namely, the automated control and programming of model systems that self-assemble into specific configurations and, on the other hand, the use of self-assembling metaphors and model systems to implement

In the last decade and especially after Adleman's experiment [1] a number of computational paradi... more In the last decade and especially after Adleman's experiment [1] a number of computational paradigms, inspired or gleaned from biochemical phenomena, are becoming of growing interest building a wealth of models, called generically Molecular Computing. New advances in, on the one hand, molecular and theoretical biology, and on the other hand, mathematical and computational sciences promise to make it possible in the near future to have accurate systemic models of complex biological phenomena. Recent advances in cellular Biology led to new models, hierarchically organised, defining a new emergent research area called Cellular Computing. P-systems represent a class of distributed and parallel computing devices of a biological type that was introduced in [14] which are included in the wider field of cellular computing. Several variants of this model have been investigated and the literature on the subject is now rapidly growing. The main results in this area show that P-systems are a very powerful and efficient computational model , , . There are variants that might be classified according to different criteria. They may be regarded as language generators or acceptors, working with strings or multisets, developing synchronous or asynchronous computation. Two main classes of P-systems can be identified in the area of membrane computing [15]: cell-like P-systems and tissue-like P-systems. The former type is inspired by the internal organization of living cells with different compartments and membranes hierarchically arranged; formally this structure is associated with a tree. Tissue P-systems have been motivated by the structure and behaviour of multicellular organisms where they form a multitude of different tissues performing various functions [2]; the structure of the system is instead represented as a graph where nodes are associated with the cells which are allowed to communicate alongside the edges of the graph.

Many aspects of Nature, Biology or even from Society have become part of the techniques and algor... more Many aspects of Nature, Biology or even from Society have become part of the techniques and algorithms used in computer science or they have been used to enhance or hybridize several techniques through the inclusion of advanced evolution, cooperation or biologically based additions. The previous NICSO workshops were held in Granada, Spain, 2006, Acireale, Italy, 2007, and in Tenerife, Spain, 2008. As in the previous editions, NICSO 2010, held in Granada, Spain, was conceived as a forum for the latest ideas and the state of the ...

Self-assembly is a distributed, asynchronous mechanism that is pervasive across natural systems w... more Self-assembly is a distributed, asynchronous mechanism that is pervasive across natural systems where hierarchical complex structures are built from the bottom-up. The lack of a centralised master plan, no external intervention, and preprogrammed interactions among entities are within its most relevant and technologically appealing properties. This paper tackles the self-assembly Wang tiles designability problem by means of artificial evolution. This research is centred in the use of tiles that are extended with rotation and probabilistic motion, and an evolutionary algorithm using the Morphological Image Analyses method as a fitness function. The obtained results support this approach as a successful engineering mechanism for the computer-aided design of self-assembled patterns.

Cellular automata (CA) are an important modelling paradigm in the natural sciences and an extreme... more Cellular automata (CA) are an important modelling paradigm in the natural sciences and an extremely useful approach in the study of complex systems. Homogeneity, massive parallelism, local cellular interactions and both synchronous and asynchronous models of rule execution are some of their most prominent features, allowing scientists to model and understand a variety of phenomena in, to name but a few, the physical, chemical, biological, social and information sciences. An ubiquitous problem related with the study of complex systems by means of CA is that of parameter identification. In some cases, analytical methods are available but in many others, due to the bottom-up complexity of the underlying processes, the best route for CA identification is through design optimization by means of a metaheuristic, such as an evolutionary algorithm. In this work we report on a systematic methodology we have developed to control the spatio-temporal behavior of a CA in order to obtain a 'designoid' target pattern. Four independent CA-based complex systems were used to assess our proposal which combines clustering, fitness distance correlation and evolutionary algorithms.

Electronic Proceedings in Theoretical Computer Science, 2010

The current investigations on hyper-heuristics design have sprung up in two different flavours: h... more The current investigations on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics. In the latter, the goal is to develop a problem-domain independent strategy to automatically generate a good performing heuristic for the problem at hand. This can be done, for example, by automatically selecting and combining different low-level heuristics into a problem specific and effective strategy. Hyper-heuristics raise the level of generality on automated problem solving by attempting to select and/or generate tailored heuristics for the problem at hand. Some approaches like genetic programming have been proposed for this. In this paper, we explore an elegant nature-inspired alternative based on self-assembly construction processes, in which structures emerge out of local interactions between autonomous components. This idea arises from previous works in which computational models of self-assembly were subject to evolutionary design in order to perform the automatic construction of user-defined structures. Then, the aim of this paper is to present a novel methodology for the automated design of heuristics by means of self-assembly.