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An Agent-based Classification Model
Conference Proceeding
Gu, F., Aickelin, U., & Greensmith, J. An Agent-based Classification Model.

The major function of this model is to access the UCI Wisconsin Breast Cancer data-set[1] and classify the data items into two categories, which are normal and anomalous. This kind of classification can be referred as anomaly detection, which discri... Read More about An Agent-based Classification Model.

Human Behavious Modelling for Discrete Event and Agent Based Simulation: A Case Study
Conference Proceeding
Majid, M., Aickelin, U., & Siebers, P. Human Behavious Modelling for Discrete Event and Agent Based Simulation: A Case Study.

This study is about the comparison of simulation techniques between Discrete Event Simulation (DES) and Agent Based Simulation (ABS). DES is one of the best-known types of simulation techniques in Operational Research. Recently, there has been an e... Read More about Human Behavious Modelling for Discrete Event and Agent Based Simulation: A Case Study.

The Application of a Dendric Cell Algorithm to a Robotic Classifier
Conference Proceeding
Oates, R., Greensmith, J., Aickelin, U., Garibaldi, J., & Kendall, G. The Application of a Dendric Cell Algorithm to a Robotic Classifier.

The dendritic cell algorithm is an immune-inspired technique for processing time-dependant data. Here we propose it as a possible solution for a robotic classification problem. The dendritic cell algorithm is implemented on a real robot and an invest... Read More about The Application of a Dendric Cell Algorithm to a Robotic Classifier.

A Multi-Agent Simulation of Retail Management Practices
Conference Proceeding
Siebers, P., Aickelin, U., Celia, H., & Clegg, C. A Multi-Agent Simulation of Retail Management Practices.

We apply Agent-Based Modeling and Simulation (ABMS) to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fac... Read More about A Multi-Agent Simulation of Retail Management Practices.

Using Intelligent Agents to Understand Management Practices and Retail Productivity
Conference Proceeding
Siebers, P., Aickelin, U., Celia, H., & Clegg, C. Using Intelligent Agents to Understand Management Practices and Retail Productivity.

Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relati... Read More about Using Intelligent Agents to Understand Management Practices and Retail Productivity.

Motif detection inspired by immune memory
Journal Article
Wilson, W., Birkin, P., & Aickelin, U. Motif detection inspired by immune memory. Lecture Notes in Artificial Intelligence, 4628, https://doi.org/10.1007/978-3-540-73922-7_24

The search for patterns or motifs in data represents an area of key interest to many researchers. In this paper we present the Motif Tracking Algorithm, a novel immune inspired pattern identification tool that is able to identify variable length unkn... Read More about Motif detection inspired by immune memory.

Simulation Optimization of the Crossdock Door Assignmnet Problem
Conference Proceeding
Aickelin, U., & Adewunmi, A. (2006). Simulation Optimization of the Crossdock Door Assignmnet Problem.

The purpose of this report is to present the Crossdock Door Assignment Problem, which involves assigning destinations to outbound dock doors of Crossdock centres such that travel distance by material handling equipment is minimized. We propose a two... Read More about Simulation Optimization of the Crossdock Door Assignmnet Problem.

Improved Squeaky Wheel Optimisation for Driver Scheduling
Conference Proceeding
Aickelin, U., Burke, E., & Li, J. Improved Squeaky Wheel Optimisation for Driver Scheduling.

This paper presents a technique called Improved Squeaky Wheel Optimisation (ISWO) for driver scheduling problems. It improves the original Squeaky Wheel Optimisation’s (SWO) effectiveness and execution speed by incorporating two additional steps of S... Read More about Improved Squeaky Wheel Optimisation for Driver Scheduling.

BioHEL: Bioinformatics-oriented Hierarchical Evolutionary Learning
Book
Bacardit, J., & Krasnogor, N. (2006). BioHEL: Bioinformatics-oriented Hierarchical Evolutionary Learning. Computer Science & IT

This technical report briefly describes our recent work in the iterative rule learning approach (IRL) of evolutionary learning/genetics-based machine learning. This approach was initiated by the SIA system. A more recent example is HIDER. Our approac... Read More about BioHEL: Bioinformatics-oriented Hierarchical Evolutionary Learning.

Modelling Immunological Memory
Book Chapter
Garrett, S., Robbins, M., Walker, J., Wilson, W., & Aickelin, U. Modelling Immunological Memory. In D. Flower, & J. Timmis (Eds.), Silico Immunology. Springer

Accurate immunological models offer the possibility of performing highthroughput experiments in silico that can predict, or at least suggest, in vivo phenomena. In this chapter, we compare various models of immunological memory. We first validate an... Read More about Modelling Immunological Memory.

Articulation and Clarification of the Dendric Cell Algorithm
Conference Proceeding
Greensmith, J., Aickelin, U., & Twycross, J. Articulation and Clarification of the Dendric Cell Algorithm.

The Dendritic Cell algorithm (DCA) is inspired by recent work in innate immunity. In this paper a formal description of the DCA is given. The DCA is described in detail, and its use as an anomaly detector is illustrated within the context of compute... Read More about Articulation and Clarification of the Dendric Cell Algorithm.