All Outputs (166)

Cooperation in Repeated Rock-Paper-Scissors Games in Uncertain Environments (2018)
Presentation / Conference Contribution
Andras, P. (2018). Cooperation in Repeated Rock-Paper-Scissors Games in Uncertain Environments. In ALIFE 2018: The 2018 Conference on Artificial Life (404-411). https://doi.org/10.1162/isal_a_00078

Cooperation among selfish individuals provides the fundamentals for social organization among animals and humans. Cooperation games capture this behavior at an abstract level and provide the tools for the analysis of the evolution of cooperation. Her... Read More about Cooperation in Repeated Rock-Paper-Scissors Games in Uncertain Environments.

Social learning and cultural evolution in artificial life (2018)
Journal Article
Marriott, C., Borg, J. M., Andras, P., & Smaldino, P. E. (2018). Social learning and cultural evolution in artificial life. Artificial Life, 24(1), 5-9. https://doi.org/10.1162/ARTL_a_00250

We describe the questions and discussions raised at the First Workshop on Social Learning and Cultural Evolution held at theArtificial Life Conference 2016 in Cancún, Mexico in July 2016. The purpose of the workshop was to assemble artificial life re... Read More about Social learning and cultural evolution in artificial life.

Random projection neural network approximation (2018)
Presentation / Conference Contribution
Andras, P. (2018). Random projection neural network approximation. In 2018 International Joint Conference on Neural Networks (IJCNN) (1-8). https://doi.org/10.1109/IJCNN.2018.8489215

Neural networks are often used to approximate functions defined over high-dimensional data spaces (e.g. text data, genomic data, multi-sensor data). Such approximation tasks are usually difficult due to the curse of dimensionality and improved method... Read More about Random projection neural network approximation.

Social learning in repeated cooperation games in uncertain environments (2018)
Journal Article
Andras, P. (2018). Social learning in repeated cooperation games in uncertain environments. Cognitive Systems Research, 51, 24-39. https://doi.org/10.1016/j.cogsys.2018.04.013

Cooperation and social learning are fundamental mechanisms that maintain social organisation among animals and humans. Social institutions can be conceptualised abstractly as cooperation games with social learning. In some cases potential cooperation... Read More about Social learning in repeated cooperation games in uncertain environments.

Reproducibility in machine Learning-Based studies: An example of text mining (2017)
Presentation / Conference Contribution
Olorisade, B. K., Brereton, P., & Andras, P. (2017). Reproducibility in machine Learning-Based studies: An example of text mining. In ICML 2017 RML Workshop: Reproducibility in Machine Learning

Reproducibility is an essential requirement for computational studies including those based on machine learning techniques. However, many machine learning studies are either not reproducible or are difficult to reproduce. In this paper, we consider... Read More about Reproducibility in machine Learning-Based studies: An example of text mining.

A robust data-driven approach to the decoding of pyloric neuron activity (2017)
Presentation / Conference Contribution
dos Santos, F., Andras, P., Collins, D., & Lam, K. (2017). A robust data-driven approach to the decoding of pyloric neuron activity. In 2017 IEEE International Workshop on Signal Processing Systems (SiPS). https://doi.org/10.1109/SiPS.2017.8110017

The combination of intra and extra-cellular recording of small neuronal circuits such as stomatogastric nervous systems of the crab (Cancer borealis) is well documented and routinely practised. Voltage sensitive dye imaging (VSDi) is a promising tech... Read More about A robust data-driven approach to the decoding of pyloric neuron activity.

Towards an Accurate Identification of Pyloric Neuron Activity with VSDi (2017)
Presentation / Conference Contribution
dos Santos, F., Andras, P., & Lam, K. (2017). Towards an Accurate Identification of Pyloric Neuron Activity with VSDi. In Artificial Neural Networks and Machine Learning – ICANN 2017 (121-128). https://doi.org/10.1007/978-3-319-68600-4_15

Voltage-sensitive dye imaging (VSDi) which enables simultaneous optical recording of many neurons in the pyloric circuit of the stomatogastric ganglion is an important technique to supplement electrophysiological recordings. However, utilising the te... Read More about Towards an Accurate Identification of Pyloric Neuron Activity with VSDi.

A multiresolution approach to the extraction of the pyloric rhythm (2017)
Presentation / Conference Contribution
dos Santos, F., Andras, P., & Lam, K. (2017, July). A multiresolution approach to the extraction of the pyloric rhythm. Presented at 2017 40th International Conference on Telecommunications and Signal Processing (TSP), Barcelona, Spain

This paper describes our work toward the development of a computationally robust methodology to identify the pyloric neurons in the stomatogastric ganglion of Cancer pagurus using voltage-sensitive dye imaging. The multi-resolution signal decompositi... Read More about A multiresolution approach to the extraction of the pyloric rhythm.

Locally Excited State–Charge Transfer State Coupled Dyes as Optically Responsive Neuron Firing Probes (2017)
Journal Article
Sirbu, D., Butcher, J. B., Waddell, P. G., Andras, P., & Benniston, A. C. (2017). Locally Excited State–Charge Transfer State Coupled Dyes as Optically Responsive Neuron Firing Probes. Chemistry - A European Journal, 23(58), 14639-14649. https://doi.org/10.1002/chem.201703366

A selection of NIR-optically responsive neuron probes was produced comprising of a donor julolidyl group connected to a BODIPY core and several different styryl and vinylpyridinyl derived acceptor moieties. The strength of the donor–acceptor interact... Read More about Locally Excited State–Charge Transfer State Coupled Dyes as Optically Responsive Neuron Firing Probes.

Open-ended evolution in cellular automata worlds (2017)
Presentation / Conference Contribution
Andras, P. (2017). Open-ended evolution in cellular automata worlds. In ECAL 2017, the Fourteenth European Conference on Artificial Life (438-445). https://doi.org/10.1162/isal_a_073

Open-ended evolution is a fundamental issue in artificial life research. We consider biological and social systems as a flux of interacting components that transiently participate in interactions with other system components as part of these systems.... Read More about Open-ended evolution in cellular automata worlds.

A systematic mapping study of empirical studies on software cloud testing methods (2017)
Presentation / Conference Contribution
Ahmad, A. A., Brereton, P., & Andras, P. (2017, July). A systematic mapping study of empirical studies on software cloud testing methods. Presented at 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), Prague, Czech Republic

Context: Software has become more complicated, dynamic, and asynchronous than ever, making testing more challenging. With the increasing interest in the development of cloud computing, and increasing demand for cloud-based services, it has become ess... Read More about A systematic mapping study of empirical studies on software cloud testing methods.

Using supervised machine learning algorithms to detect suspicious URLs in online social networks (2017)
Presentation / Conference Contribution
Al-Janabi, M., Quincey, E. D., & Andras, P. (2017, July). Using supervised machine learning algorithms to detect suspicious URLs in online social networks. Presented at 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, Sydney, Australia

The increasing volume of malicious content in social networks requires automated methods to detect and eliminate such content. This paper describes a supervised machine learning classification model that has been built to detect the distribution of m... Read More about Using supervised machine learning algorithms to detect suspicious URLs in online social networks.

A systematic analysis of random forest based social media spam classification (2017)
Presentation / Conference Contribution
Al-Janabi, M., & Andras, P. (2017, August). A systematic analysis of random forest based social media spam classification. Presented at NSS: International Conference on Network and System Security, Helsinki, Finland

Recently random forest classification became a popular choice machine learning applications aimed to detect spam content in online social networks. In this paper, we report a systematic analysis of random forest classification for this purpose. We as... Read More about A systematic analysis of random forest based social media spam classification.

Reproducibility of studies on text mining for citation screening in systematic reviews: evaluation and checklist (2017)
Journal Article
Olorisade, B. K., Brereton, P., & Andras, P. (2017). Reproducibility of studies on text mining for citation screening in systematic reviews: evaluation and checklist. Journal of Biomedical Informatics, 73, 1-13. https://doi.org/10.1016/j.jbi.2017.07.010

Context Independent validation of published scientific results through study replication is a pre-condition for accepting the validity of such results. In computation research, full replication is often unrealistic for independent results validation... Read More about Reproducibility of studies on text mining for citation screening in systematic reviews: evaluation and checklist.

Reporting Statistical Validity and Model Complexity in Machine Learning based Computational Studies (2017)
Presentation / Conference Contribution
Olorisade, B. K., Brereton, P., & Andras, P. (2017, June). Reporting Statistical Validity and Model Complexity in Machine Learning based Computational Studies. Presented at EASE'17: 21st International Conference on Evaluation and Assessment in Software Engineering, Karlskrona, Sweden

Background:: Statistical validity and model complexity are both important concepts to enhanced understanding and correctness assessment of computational models. However, information about these are often missing from publications applying machine lea... Read More about Reporting Statistical Validity and Model Complexity in Machine Learning based Computational Studies.

High-dimensional function approximation with neural networks for large volumes of data (2017)
Journal Article
Andras, P. (2018). High-dimensional function approximation with neural networks for large volumes of data. IEEE Transactions on Neural Networks and Learning Systems, 29(2), 500-508. https://doi.org/10.1109/TNNLS.2017.2651985

Approximation of high-dimensional functions is a challenge for neural networks due to the curse of dimensionality. Often the data for which the approximated function is defined resides on a low-dimensional manifold and in principle the approximation... Read More about High-dimensional function approximation with neural networks for large volumes of data.

The Infiniteness of Open Ended Evolution (2016)
Presentation / Conference Contribution
Andras, P. (2016). The Infiniteness of Open Ended Evolution. In OEE2: The Second Workshop on Open-Ended Evolution

Biological and social systems are considered as a flux of interacting components that transiently participate in interactions with other system components as part of the system. This suggests that any simulated system undergoing open ended evolution... Read More about The Infiniteness of Open Ended Evolution.

Modelling the restoration of activity in a biological neural network (2016)
Presentation / Conference Contribution
Dos Santos, F., Steyn, J. S., & Andras, P. (2016). Modelling the restoration of activity in a biological neural network. In 2016 International Joint Conference on Neural Networks (IJCNN) (4672-4679). https://doi.org/10.1109/IJCNN.2016.7727813

Understanding the mechanisms of restoration of activity in biological neural systems following exposure to damage is key for design of future neuro-prosthetic devices and restorative treatments. The pyloric rhythm network within the crustacean stomat... Read More about Modelling the restoration of activity in a biological neural network.

Analysis of the dynamics of temporal relationships of neural activities using optical imaging data (2016)
Journal Article
Steyn, J. S., & Andras, P. (2017). Analysis of the dynamics of temporal relationships of neural activities using optical imaging data. Journal of Computational Neuroscience, 42, 107-121. https://doi.org/10.1007/s10827-016-0630-8

The temporal relationship between the activities of neurons in biological neural systems is critically important for the correct delivery of the functionality of these systems. Fine measurement of temporal relationships of neural activities using mic... Read More about Analysis of the dynamics of temporal relationships of neural activities using optical imaging data.

Unsupervised home monitoring of Parkinson's disease motor symptoms using body-worn accelerometers (2016)
Journal Article
Fisher, J. M., Hammerla, N. Y., Ploetz, T., Andras, P., Rochester, L., & Walker, R. W. (2016). Unsupervised home monitoring of Parkinson's disease motor symptoms using body-worn accelerometers. Parkinsonism and Related Disorders, 33, 44-50. https://doi.org/10.1016/j.parkreldis.2016.09.009

Introduction Current PD assessment methods have inherent limitations. There is need for an objective method to assist clinical decisions and to facilitate evaluation of treatments. Accelerometers, and analysis using artificial neural networks (ANN),... Read More about Unsupervised home monitoring of Parkinson's disease motor symptoms using body-worn accelerometers.