George G. Mitchell

Realizeit - Chicago IL & Dublin IE

The evaluation of signal transduction networks is a constantly advancing challenge, which requires the use of the latest modelling techniques to capture system dynamics and properties. State of the art modelling techniques are drawn from a highly diverse range of different research areas, e.g., mathematics, computer science, statistics, etc. As a r...

This paper documents the work in progress in creating a new Intelligent Learning System. The paper introduces the issues of relevance when developing such systems. It examines briefly the state of the art followed by key approaches to addressing the major research questions in the field. We introduce the Realise it system outlining the philosophy b...

We examine a potential role of signalling crosstalk in Artificial Cell Signalling Networks (ACSNs). In this research, we regard these ACSNs as subsets of collectively autocatalytic (i.e., organizationally closed) reaction networks being able to both self-maintain and to carry out a distinct signal processing function. These signalling crosstalk phe...

The simulation and designing of precise models of biochemical processes is one of the key aims of Computational Systems Biology [1]. In this paper we are concerned with the simulation and modelling of one form of biochemical network Cell Signalling Networks (CSNs). CSNs are networks of interacting molecules naturally occurring in living cells [2],...

This work investigates closure in Cell Signaling Networks, which is one research area within the ESIGNET project. We employ a string-based Artificial Chemistry based on Holland’s broadcast language (Molecular Classifier System, Broadcast Language, or MCS.b). We present a series of experiments focusing on the emergence and evolution of self-maintain...

This paper is concerned with the modeling and evolving of Cell Signaling Networks (CSNs) in silico. CSNs are complex biochemical networks responsible for the coordination of cellular activities. We examine the possibility to computationally evolve and simulate Artificial Cell Signaling Networks (ACSNs) by means of Evolutionary Computation technique...

Multi-level selection has proven to be an affective mean to provide resistance against parasites for catalytic networks (Cronhjort and Blomberg, 1997). One way to implement these multi-level systems is to group molecules into several distinct compartments (cells) which are capable of cellular division (where an offspring cell replaces another cell)...

In this paper we present a novel cost benefit operator that assists multi level genetic algorithm searches. Through the use of the cost benefit operator, it is possible to dynamically constrain the search of the base level genetic algorithm, to suit the user's requirements. Initially we review meta-evolutionary (multi-level genetic algorithm) appro...

Current approaches within the ESIGNET project (ESIGNET: Evolving Cell Signaling Networks in Silico), an EU FP6 project (contract number 12789 http://www.esignet.net) have used multilevel Evolutionary Algorithms (EA) to assist in the understanding of evolution and complexity of biochemical networks. These systems have utilized meta-level EAs to evol...

Complex Adaptive Systems (CAS) are dynamical networks of interacting agents which as a whole determine the behavior, adaptivity and cognitive ability of the system. CAS are ubiquitous and occur in a variety of natural and artificial systems (e.g., cells, societies, stock markets). To study CAS, Holland proposed to employ an agent-based system in wh...

This thesis addresses the issues associated with conventional genetic algorithms (GA) when applied to hard optimisation problems. In particular it examines the problem of selecting and implementing appropriate genetic operators in order to meet the validity constraints for constrained optimisation problems. The problem selected is the travelling sa...

We present a novel cost benefit operator that assists multi levelgenetic algorithm searches. Through the use of the cost benefitoperator, it is possible to dynamically constrain the search of thebase level genetic algorithms, to suit the users requirements. We note that the current literature has abundant studies on metaevolutionary GAs, however th...

The Broadcast Language is a programming formalism devised by Holland in 1975, which aims at improving the efficiency of Genetic Algorithms (GAs) during long-term evolution. The key mechanism of the Broadcast Language is to allow GAs to employ an adaptable problem representation. Fixed problem encoding is commonly used by GAs but may limit their per...

Nature is a source of inspiration for computational techniques which have been successfully applied to a wide variety of complex application domains. In keeping with this we examine Cell Signaling Networks (CSN) which are chemical networks responsible for coordinating cell activities within their environment. Through evolution they have become high...

Complex Adaptive Systems (CAS) are dynamical networks of interacting agents occurring in a variety of natural and artificial systems (e.g. cells, societies, stock markets). These complex systems have the ability to adapt, evolve and learn from experience. To study CAS, Holland proposed to employ agent-based systems in which Learning Classifier Syst...

Protocells are hypothesised as a transitional phase in the origin of life, prior to the evolution of fully functional prokaryotic cells. The work reported here is being done in the context of the PACE project, which is investigating the fabrication of artificial protocells de novo. We consider here the important open question of whether or how arti...

Nature is a source of inspiration for computational techniques which have been successfully applied to a wide variety of complex application domains. In keeping with this we examine Cell Signaling Networks (CSN) which are chemical networks responsible for coordinating cell activities within their environment. Through evolution they have become high...

Cell Signaling networks (CSNs) are bio-chemical systems of interacting molecules in cells. Typically, these systems take as inputs chemical signals generated within the cell or communicated from outside. These trigger a cascade of chemical reactions that result in changes of the state of the cell and (or) generate some chemical output, such as prok...

Cell Signaling Networks(CSN) are complex bio-chemical networks which, through evolution, have become highly efficient for governing critical control processes such as immunological responses, cell cycle control or homeostasis. From a computational point of view, modeling Artificial Cell Signaling Networks (ACSNs) in silico may provide new ways to d...

All processes of life are dominated by networks of interacting biochemical components. The purpose of modeling these networks is manifold. From a theoretical point of view it allows the exploration of network structures and dynamics, to find emergent properties or to explain the organization and evolution of networks. From a practical point of view...

The EU FP6 Integrated Project PACE ('Programmable Artificial Cell Evolution') is investigating the creation, de novo, of chemical 'protocells'. These will be minimal 'wetware' chemical systems integrating molecular information carriers, primitive energy conversion (metabolism) and containment (membrane). Ultimately they should be capable of autonom...

Applied research is, by necessity, a distributed, collaborative process. To be useful, research methodologies must not only be applicable in such an environment, but must also be adaptive to the needs of human resources and specific research area requirements. This paper introduces eXtreme Researching (XR), an adaptation of eXtreme Programming (XP)...

This paper introduces our Distributed Parameter-Less Genetic Algorithm and highlights the practical and economical motivations of such a system. With the Distributed Parameter-Less GA users do not have to perform trial and error experiments to find suitable parameter settings for the Genetic Algorithm. The users also achieve economically viable res...

In this paper we present the outcome of a sets of experiments to evaluate the effectiveness of a new adjunct genetic operator GeneRepair. This operator was developed to correct invlaid tours which may be generated following crossover or mutation of our particular implementation of the genetic algorithm. Following implementation and testing of our g...

This case study explores teaching and learning on an undergraduate computer science and software engineering degree course called Real World Software Engineering. It describes the design, teaching and continuous refinement of the course from an initial concept based on learning-by-doing, to a fully structured course grounded in the Problem-based Le...

This paper briefly explores the role of experiential learning in software engineering education, focusing on Problem-based learning. An existing assessment strategy for grading individual students in a small group Problem-based learning setting is described. Although the student grades obtained may be a reflection of the course success, and standar...

In this paper we present the outcome of two recent sets of experiments to evaluate the effectiveness of a new adjunct genetic operator GeneRepair. This operator was developed to correct invlaid tours which may be generated following crossover or mutation of our particular implementation of the genetic algorithm. Following implementation and testing...

This paper describes the application of Problem-based learning (PBL) to the design and implementation of an Ecommerce web site by small groups of software engineering students. This work is part of a real-world software engineering course, taught to pre-internship students. The use of PBL has gained significant interest since its inception in the l...

A PROBLEM-DRIVEN APPROACH FOR TEACHING SOFTWARE ENGINEERING TO UNDERGRADUATE STUDENTS IS ENTERING ITS THIRD YEAR AT THE DEPARTMENT OF COMPUTER SCIENCE AT NUI, MAYNOOTH.

We present a design pattern for improving the reliability of forwarding failures within protocol processes and kernel routers. Our design pattern makes use of a localised Invisible Recovery (IR) process and a technique for optimising the Kernel process. We evaluate the current techniques that provide recovery within network systems; by doing so we...

In this paper we present the advances we have made in our network fault tolerant computing project [1]. We examine the problems of failures within network communications and telecom systems and outline the usefulness of our localised Invisible Recovery (IR) solution. We evaluate the current techniques [2,3,8] that provide recovery within distribute...

In this paper we examine the problem of failures within network communications and telecom systems and outline a localised Invisible Recovery solution to such systems. We introduce a new approach that makes use of an envelope surrounding an unchanged software protocol layer, which is running as an independent process. This envelope stores just suff...

In this paper we present two sets of empirical data evaluating the performance of a new Cleanup operator for evolutionary approaches to the travelling salesman problem (TSP). For raw data we have used standard road mileage charts of the USA, Great Britain and Ireland, which enable us to generate a reference table with appropriate city to city dista...