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WIVACE2012
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Session 1: |
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Experimental perspectives for a chemical communication between synthetic and natural cells |
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Abstract: The recent advancements in semi-synthetic minimal cell (SSMC) technology paves the way to several interesting scenarios that span from basic scientific advancements to applications in biotechnology. In this short article we discuss the relevance of establishing chemical communication between synthetic and natural cells as an important conceptual question, and then discuss it as a new bio/chem-information & communication technology (bio/chem-ICT). At this aim, the state-of-the-art of SSMCs technology is shortly reviewed, and a possible experimental approach based on bacteria quorum sensing (QS) mechanisms is proposed and discussed. |
BibTeX:
@inproceedings{stano-wivace-12,
author = {Pasquale Stano and Giordano Rampioni and Luisa Damiano and Francesca D'Angelo and Paolo Carrara and Livia Leoni and Luigi Luisi},
title = {Experimental perspectives for a chemical communication between synthetic and natural cells},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--12},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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The Effects of Multivalency and Kinetics in Nanoscale Search by Molecular Spiders |
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Abstract: Molecular spiders are nanoscale walkers made with catalytic DNA legs attached to a rigid body. They move over a surface of DNA substrates, cleaving them and leaving behind product DNA strands, which they are able to revisit. The legs cleave and detach from substrates more slowly than they detach from products. This difference in residence time and the presence of multiple legs make a spider move differently from an ordinary random walker. The number of legs, and their lengths, can be varied, and this defines how a spider moves on the surface, i.e., its gait. In this work we define an abstract model of molecular spiders. Using Kinetic Monte Carlo simulation, we study how efficiently spiders with various gaits are able to find specific targets on a two-dimensional lattice. Multi-legged spiders with certain gaits can find the targets faster than regular random walkers. The search performance of spiders depends on both their gait and the kinetic rate r describing the relative substrate/product “stickiness”. Spiders with gaits that allow more freedom for leg movements find their targets faster than spiders with more restrictive gaits. For every gait, there is an optimal value of r that minimizes the time to find all target sites. |
BibTeX:
@inproceedings{semenov-wivace-12,
author = {Oleg Semenov and Darko Stefanovic and Milan Stojanovic},
title = {The Effects of Multivalency and Kinetics in Nanoscale Search by Molecular Spiders},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--12},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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The influence of different kinetic rates on the dynamics of a simple model of catalytic reaction network |
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Abstract: An ODE-based model of a simple catalytic reaction network is discussed, with particular attention to the influence of the kinetic rates of the various reactions on the overall dynamical behavior. Several distinct scenarios are described and analyzed, highlighting the importance of the fine tuning of the kinetic parameters in regard to the competition for survival of different dynamical structures, i.e. autocatalytic cycles, on the one hand, and linear reaction chains, on the other, which access the same limited resources. Finally, the importance of a possible compartmentalization of this dynamical system within protocell-like structures is discussed, with explicit regard to the competitive advantage that is supposed to characterize the dynamics of autocatalyitic cycles. |
BibTeX:
@inproceedings{filisetti-wivace-12,
author = {Alessandro Filisetti and Alex Graudenzi},
title = {The influence of different kinetic rates on the dynamics of a simple model of catalytic reaction network},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--12},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Session 2: |
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An Evolutionary Approach to Grid Computing Agents |
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Abstract: The Organic Computing initiative aims at introducing new, self-organising algorithms in order to cope better with the complexity of today's systems. One approach to self-organisation is the introduction of agents which are able to continuously adapt their behaviour to changing environmental conditions and thus collectively create an efficient and robust system. In this paper, we introduce an evolutionary approach to an agent which acts autonomously in a Desktop Grid system. The evolutionary agent is defined by ten chromosomes defining its behaviour. If two agents interact, the inferior agent copies a part of the genes of the more successful agent. Therefore, the most successful gene combination will spread throughout the network. |
BibTeX:
@inproceedings{bernard-wivace-12,
author = {Yvonne Bernard and Lukas Klejnowski and David Bluhm and Jörg Hähner and Christian Müller-Schloer},
title = {An Evolutionary Approach to Grid Computing Agents},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--12},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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A bio-inspired learning signal for the cumulative learning of different skills |
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Abstract: Building artificial agents able to autonomously learn new skills and to easily adapt in different and complex environments is an important goal for robotics and machine learning. We propose that providing artificial agents with a learning signal that resembles the characteristic of the phasic activations of dopaminergic neurons would be an advancement in the development of more autonomous and versatile systems. In particular, we suggest that the particular composition of such a signal, determined both by intrinsic and extrinsic reinforcements, would be suitable to improve the implementation of cumulative learning. To validate our hypothesis we performed some experiments with a simulated robotic system that has to learn different skills to obtain rewards. We compared different versions of the system varying the composition of the learning signal and we show that only the system that implements our hypothesis is able to reach high performance in the task. |
BibTeX:
@inproceedings{santucci-wivace-12,
author = {Vieri Giuliano Santucci and Gianluca Baldassarre and Marco Mirolli},
title = {A bio-inspired learning signal for the cumulative learning of different skills},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--12},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Development of categorization abilities in evolving embodied agents : a study of internal representations with external social inputs |
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Abstract: The present paper investigates how embodied and situated agents perform tasks that require skills of categorization. The agents are artificially created by an adaptation process. The task is to categorize different shapes of objects using sensory-motor and linguistic input. Results show that the autonomous agents are able to solve the categorization task by integrating the sensory-motor experienced states and employing "linguistic" input from the environment. This shows that autonomous agents are able to develop some "emerging" abilities by exploiting the information present in the environment in order to recognize and discriminate objects. Autonomous agents also exhibit a "social" behavior, because they are able to categorize the objects in the environment, even when external inputs are unavailable. The purpose of this work is to prove the theoretical hypothesis that the "social" information (external labels), deriving from another agent or from the trainer, facilitates individual capacity to categorize, by the creation of internal representations. |
BibTeX:
@inproceedings{pugliese-wivace-12,
author = {Francesco Pugliese},
title = {Development of categorization abilities in evolving embodied agents : a study of internal representations with external social inputs},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--13},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Collective Adaptive Agents as Techniques to build-up Edutainments Systems |
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Abstract: Artificial Life since its first inception has changed the way many scientists use to design and carry out experiments in different disciplines such as psychology, sociology, biology, chemistry and the like. In the last two decades Artificial Life has become a great tool to shed light on different and profound scientific questions, however its potential in educational environments has not been completely exploited. In this article we describe two case studies in which Artificial Life has been used as a powerful learning tool for the theory of evolution, BreedBot and co. (actually Breedbot, BestBot and BrainFarm), and for group dynamics, Learn2Lead. BreedBot and its sequels Bestbot and Brainfarm are integrated hardware/software platforms that allow users to evolve a robot able to explore effectively a customized environment made up of walls and colored obstacles. Each robot is controlled by an artificial neural network whose parameters are encoded in a genetic string. Users can opt either for a natural or an artificial selection. In Learn2Lead, each learner manages a simulated team of employees which competes against other teams to maximize its objectives (e.g. profit, volume of services delivered, customer satisfaction). Both serious games provide children and older users a very easy tool to understand complex concepts like evolution an group dynamics within a playful learning context. |
BibTeX:
@inproceedings{miglino-wivace-12,
author = {Orazio Miglino and Onofrio Gigliotta and Massimiliano Schembri and Andrea Di Ferdinando},
title = {Collective Adaptive Agents as Techniques to build-up Edutainments Systems},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--13},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Session 3: |
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Automatic Design of Boolean Networks for Modelling Cell Differentiation |
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Abstract: A mathematical model based on Random Boolean Networks has been recently proposed to describe the main features of cell differentiation. The model captures in a unique framework all the main phenomena involved in cell differentiation and can be subject to experimental testing. A prominent role in the model is played by cellular noise, which somehow controls the cell ontogenetic process from the stem, totipotent state to the mature, completely differentiated one. Noise is high in stem cells and it decreases while the cell undergoes the differentiation process. A limitation of the current mathematical model is that Random Boolean Networks, as an ensemble, are not endowed with the property of showing a smooth relation between noise level and the differentiation stages of cells. In this work, we show that it is possible to generate an ensemble of Boolean networks that can accomplish such requirement, while keeping the other main relevant statistical features of classical Random Boolean Networks. This ensemble is designed by means of an optimisation process, in which a stochastic local search optimises an objective function which accounts for the requirements the network ensemble has to fulfil. |
BibTeX:
@inproceedings{benedettini-wivace-12,
author = {Stefano Benedettini and Andrea Roli and Roberto Serra and Marco Villani},
title = {Automatic Design of Boolean Networks for Modelling Cell Differentiation},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--12},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Regulatory Traits in Cultural Evolution |
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Abstract: We call "regulatory traits" those cultural traits that are transmitted through cultural interactions and, at the same time, change individual behaviors directly influencing the outcome of future cultural interactions. The cultural dynamics of some of those traits are studied through simple simulations. In particular, we consider the cultural evolution of traits determining the propensity to copy, the number of potential demonstrators from whom one individual may copy, and conformist versus anti–conformist attitudes. Our results show that regulatory traits generate peculiar dynamics that may explain complex human cultural phenomena. We discuss how the existence and importance of regulatory traits in cultural evolution impact on the analogy between genetic and cultural evolution and therefore on the possibility of using evolutionary biology–inspired models to study human cultural dynamics. |
BibTeX:
@inproceedings{acerbi-wivace-12,
author = {Alberto Acerbi and Stefano Ghirlanda and Magnus Enquist},
title = {Regulatory Traits in Cultural Evolution},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--9},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Neuro-Evolutionary Modeling of the Milan Stock Exchange for Intraday Trading |
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Abstract: We investigate the correlations among the intraday prices of the major stocks of the Milan Stock Exchange by means of a neuroevolutionary modeling method. In particular, the method used to approach such problem is to apply a very powerful natural computing analysis tool, namely evolutionary neural networks, based on the joint evolution of the topology and the connection weights together with a novel similarity-based crossover, to the analysis of a financial intraday time series expressing the stock quote variations of the FTSE MIB components. We show that it is possible to obtain extremely accurate models of the variations of the price of one stock based on the price variations of the other components of the stock list, which may be used for statistical arbitrage. The approach has been also validated by implementing a simple trading system that performs decisions by considering the results computed by the algorithm. |
BibTeX:
@inproceedings{azzini-wivace-12,
author = {Antonia Azzini and Mauro Dragoni and Andrea G. B. Tettamanzi},
title = {Neuro-Evolutionary Modeling of the Milan Stock Exchange for Intraday Trading},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--12},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Session 4: |
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Nature-inspired Methods for Monitoring Applications with Time-Evolving Data |
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Abstract: Supporting real-time monitoring of large amount of information from diverse information sources is receiving an increasing demand because of the advances in data gathering and communication technologies. In this paper we propose to use a density-based clustering algorithm, built on the Multiple Species Flocking model, for the monitoring of large volume of streaming data, generated from numerous applications such as machine monitoring, health monitoring, sensor networks, speech recognition. The approach has two main characteristics that make it particularly apt for real life monitoring applications. The first is that the clustering results are available on demand at any time. The second one is that clusters can be visually tracked during their generation. This enables a user to visually detect changes in cluster distribution and gives him insights about the evolving nature of clusters, and thus when to eventually take actions and decisions in real time because of the changed conditions. |
BibTeX:
@inproceedings{pizzuti-wivace-12,
author = {Clara Pizzuti and Giandomenico Spezzano},
title = {Nature-inspired Methods for Monitoring Applications with Time-Evolving Data},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--12},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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A Statistical Study of Concurrent Differential Evolution on Multi-core CPUs |
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Abstract: In order to utilize multi-core CPUs, a concurrent program of the latest evolutionary algorithm, i.e., Differential Evolution (DE), is described. The concurrent program of DE is based on a programming model known as "MapReduce" and named Concurrent DE (CDE). In this paper, two implementation techniques of CDE, namely CDE/D and CDE/S, are presented and compared in the quality of the solutions. Through the numerical experiments and the statistical tests conducted on two kinds of popular multi-core CPUs, it is shown that CDE/D is superior to CDE/S in the quality of the solutions obtained by CDE, however CDE/D is inferior to CDE/S in the execution time of CDE. |
BibTeX:
@inproceedings{tagawa-wivace-12,
author = {Kiyoharu Tagawa},
title = {A Statistical Study of Concurrent Differential Evolution on Multi-core CPUs},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--12},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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A Genetic Optimization Technique for the Strategic Use of Renewable Energy Supply |
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Abstract: This paper presents a new strategy to solve the optimal constrained problem of scheduling the work phases of households. In particular, the real-world application refers to a new generation of appliances having advanced communications and networking features and fed by an opportune system chasing the curve of availability of locally produced renewable energy. The proposed work allows appliances to adapt their operations to the current state by activating low power mode and waiting for the right time to start a cycle with high consumption, for example, when the system delivers more power. The goal is to find a solution to make these houses energy self-sufficient, allowing the use only when there is availability. The constrained optimization is solved by the well known Genocop III, proposed by Michalewicz [1]. The results of the experimental implemented solution reveal good performance and accuracy and are presented, at the end of this paper, by means of a prototype of a graphical interface that shows the expected trend of generated power, the consumption power trend of scheduled activities and the expected consumption power trend of households. |
BibTeX:
@inproceedings{bevilacqua-wivace-12,
author = {Vitoantonio Bevilacqua and Domenico Buongiorno and Domenico Chiaradia and Nicola Longo and Nicola Savino and Nicangela Bevilacqua and Giuseppe Rana},
title = {A Genetic Optimization Technique for the Strategic Use of Renewable Energy Supply},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--12},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Adaptive ε-Ranking and Distribution Search on Evolutionary Many-objective Optimization |
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Abstract: In this work, we study the effectiveness of Adaptive ε-Ranking for distribution search in the context of many-objective optimization. Adaptive -Ranking re-classifies sets of non-dominated solutions using iteratively a randomized sampling procedure that applies ε-dominance with a mapping function f (x) →ε f'(x) to bias selection towards the distribution of solutions implicit in the mapping. We analyze the effectiveness of Adaptive ε-Ranking with three linear mapping functions for ε-dominance and study the importance of recombination to properly guide the algorithm towards the distribution we seek to find. As test problems, we use functions of the DTLZ family with M = 6 objectives, varying the number of variables N from 10 to 50. |
BibTeX:
@inproceedings{aguirre-wivace-12,
author = {Hernan Aguirre and Akira Oyama and Kiyoshi Tanaka},
title = {Adaptive ε-Ranking and Distribution Search on Evolutionary Many-objective Optimization},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--12},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Session 5: |
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What mechanisms underlie dyadic cooperation? A study with neuro-robotics models. |
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Abstract: Cooperation allows individuals to reach goals that one single cannot achieve. In ethological studies the mechanisms of cooperation have been widely investigated; new experimental paradigms are now introduced in controlled environments to simplify the approach and to go deep inside the strategies of cooperation. One of these experimental paradigms is the "loose string task", for example used with chimpanzees and birds. Analyzing the strategies and the mechanisms used by artificial organisms to perform a cooperation task, we observed that vision can help agents to solve the problem better than communication. |
BibTeX:
@inproceedings{pugliese2-wivace-12,
author = {Francesco Pugliese and Michela Ponticorvo},
title = {What mechanisms underlie dyadic cooperation? A study with neuro-robotics models. },
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--6},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Honest vs Cheating Bots in PATROL-based Real-Time Strategy MMOGs |
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Abstract: The increasing success of massively multi-player online games (MMOGs) is due to the fact that they allow players to explore huge virtual worlds and to interact in many different ways, either cooperating or competing. To support the implementation of ultra-scalable real-time strategy MMOGs, we are developing a middleware, called PATROL, that is based on a structured peer-to-peer overlay scheme. Among other features, PATROL provides AI-based modules to detect cheating attempts, that the decentralized communication infrastructure may favor. In this paper we illustrate how we implemented honest and cheating autonomous players (bots). In particular, we show how honest bots can detect cheating bots in real-time, thanks to strategies based on neural networks. |
BibTeX:
@inproceedings{sebastio-wivace-12,
author = {Stefano Sebastio and Michele Amoretti and Jose Raul Murga and Marco Picone and Stefano Cagnoni},
title = {Honest vs Cheating Bots in PATROL-based Real-Time Strategy MMOGs},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--11},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Poster Session: |
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Termite Retinex: A Novel Implementation based on a Colony of Agents |
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Abstract: The Retinex algorithm originally presented by Land and McCann uses random paths to explore the image. Throughout the decades, many versions of the Retinex algorithm have been proposed, mainly differing in the way they explore the image, with e.g. random paths, random samples, convolution masks, and variational formulations. In this paper, we propose a step back towards the origin, replacing random paths by traces of specialized ants swarm, here called termites. In presenting the spatial characteristics of the proposed method we discuss differences in path exploration with other Retinex implementations. Two experiments on nine images with 20 observers have been carried out and the results indicate an higher preference of our proposal with respect to the original ones and a previous implementation of Retinex. |
BibTeX:
@inproceedings{simone-wivace-12,
author = {Gabriele Simone and Giuseppe Audino and Ivar Farup and Alessandro Rizzi},
title = {Termite Retinex: A Novel Implementation based on a Colony of Agents},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--11},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Emerging social search paradigms: can we learn from ants? |
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Abstract: In a world of an abundance of data, calculation of relevance is crucial for all search engines. Google’s success with their PageRank algorithm proved this. A fundamental part of PageRank is to prioritize pages that are linked to by many other pages. But "relevance" is difficult to compute. While Google’s definition works well and satisfy many users it has the disadvantage that it is in principle based on a static view of the Web. Important sites will be more important, and many new and interesting sites may get a low priority. To avoid this problem we aim at describing relevance in a social and dynamic way. The idea is taken from biology: from the way ants forage for food. |
BibTeX:
@inproceedings{malizia-wivace-12,
author = {Alessio Malizia and Kai Olsen},
title = {Emerging social search paradigms: can we learn from ants?},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--4},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Parallel Optimization with Mutation Operator for The Quadratic Assignment Problem |
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Abstract: Recombination operator crossover is a tool that is widely used to obtain near optimal solutions for larger problem instances of the Quadratic Assignment Problem (QAP), whereas, the mutation operator is the less preferred tool. However, due to its low disruptive nature the mutation operator does have a great potential to solve the QAP. In this study we compared the performance of the mutation operator with the well-known crossover operators that are designed for use with the QAP. The mutation operator works by swapping values iteratively and outperforms most of the well-known crossovers. We conclude that, as reported to date, the mutation operator can provide either the optimum or very close to the best available solution for problem instances in the QAP library. |
BibTeX:
@inproceedings{dokeroglu-wivace-12,
author = {Tansel Dokeroglu and Umut Tosun and Ahmet Cosar},
title = {Parallel Optimization with Mutation Operator for The Quadratic Assignment Problem},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--11},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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Learning Financial Agent based Simulator: Simulated Annealing as an Optimizer for Simulation Parameters |
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Abstract: Integrating agent based modeling with machine learning results in a promising methodology to model the behavior of financial markets. We report in this paper an experimental study of our learning system L-FABS showing how it can acquire models for financial time series. |
BibTeX:
@inproceedings{neri-wivace-12,
author = {Filippo Neri},
title = {Learning Financial Agent based Simulator: Simulated Annealing as an Optimizer for Simulation Parameters},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--4},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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A Neuro-Evolutionary Approach to Electrocardiographic Signal Classification |
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Abstract: This work presents an evolutionary ANN classifier system as an heart beat classification algorithm suitable for implementation on the PhysioNet/Computing in Cardiology Challenge 2011 [7], whose aim is to develop an efficient algorithm able to run within a mobile phone, that can provide useful feedback in the process of acquiring a diagnostically useful 12-lead Electrocardiography (ECG) recording. The method used in such a problem is to apply a very powerful natural computing analysis tool, namely evolutionary neural networks, based on the joint evolution of the topology and the connection weights together with a novel similarity-based crossover. The work focuses on discerning between usable and unusable electrocar- diograms tele-medically acquired from mobile embedded devices. A pre-processing algorithm based on the Discrete Fourier Trasform has been applied before the evolutionary approach in order to extract the ECG feature dataset in the frequency domain. Finally, a series of tests has been carried out in order to evaluate the performance and the accuracy of the classifier system for such a challenge. |
BibTeX:
@inproceedings{azzini2-wivace-12,
author = {Antonia Azzini and Mauro Dragoni and Andrea G. B. Tettamanzi},
title = {A Neuro-Evolutionary Approach to Electrocardiographic Signal Classification},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--11},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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A preliminary study on BN-robots' dynamics |
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Abstract: Boolean network robotics concerns the use of Boolean networks as robot programs. In this brief contribution, we outline preliminary results on the analysis of the dynamics of BN-robots trained to accomplish a composite task. We find that the successful performing robots, which show the capability of robustly attaining the learned behaviours while adapting to new tasks to perform, are characterised by both number of fixed points and complexity higher than those of unsuccessful ones. These results are in accordance with the conjecture that systems able to balance robustness and evolvability work at the border between order and chaos and may suggest improvements to the automatic design of robot programs. |
BibTeX:
@inproceedings{roli-wivace-12,
author = {Andrea Roli and Stefano Benedettini and Mauro Birattari and Carlo Pinciroli and Roberto Serra and Marco Villani},
title = {A preliminary study on BN-robots' dynamics},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--4},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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A multiscale model of intestinal crypts dynamics |
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Abstract: Intestinal crypts are multicellular structures the properties of which have been partially characterized, both in the "normal" and in the “transformed†development. Only in the last years there has been an increasing interest in using mathematical and computational models to achieve new insights from a "systems point-of-view". However, the overall picture lacks of a general model covering all the key distinct processes and phenomena involved in the activity of the crypt. Here we propose a new multiscale model of crypt dynamics combining Gene Regulatory Networks at the intra-cellular level with a morphological model comprising spatial patterning, cell migration and crypt homeostasis at the inter-cellular level. The intra-cellular model is a Noisy Random Boolean Network ruling cell growth, division rate and lineage commitment in terms of emergent properties. The inter-cellular spatial dynamics is an extension of the Cellular Potts Model, a statistical mechanics model in which cells are represented as lattice sites in a 2D cellular automaton successfully used to model homeostasis in the crypts. |
BibTeX:
@inproceedings{graudenzi-wivace-12,
author = {Alex Graudenzi and Giulio Caravagna and Giovanni De Matteis and Giancarlo Mauri and Marco Antoniotti},
title = {A multiscale model of intestinal crypts dynamics},
booktitle = {Proc. of the Italian Workshop on Artificial Life and Evolutionary Computation },
year = {2012},
pages = {1--13},
note = {Published on CD, isbn 978-88-903581-2-8},
}
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