2013 13th UK Workshop on Computational Intelligence (UKCI)最新文献

How clumpy is my image? Evaluating crowdsourced annotation tasks 我的图像有多粗糙?评估众包注释任务

2013 13th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2013-10-31 DOI: 10.1109/UKCI.2013.6651298

Hugo Hutt, R. Everson, Murray Grant, John Love, George R. Littlejohn

{"title":"How clumpy is my image? Evaluating crowdsourced annotation tasks","authors":"Hugo Hutt, R. Everson, Murray Grant, John Love, George R. Littlejohn","doi":"10.1109/UKCI.2013.6651298","DOIUrl":"https://doi.org/10.1109/UKCI.2013.6651298","url":null,"abstract":"The use of citizen science to obtain annotations from multiple annotators has been shown to be an effective method for annotating datasets in which computational methods alone are not feasible. The way in which the annotations are obtained is an important consideration which affects the quality of the resulting consensus estimates. In this paper, we examine three separate approaches to obtaining scores for instances rather than merely classifications. To obtain a consensus score annotators were asked to make annotations in one of three paradigms: classification, scoring and ranking. A web-based citizen science experiment is described which implements the three approaches as crowdsourced annotation tasks. The tasks are evaluated in relation to the accuracy and agreement among the participants using both simulated and real-world data from the experiment. The results show a clear difference in performance between the three tasks, with the ranking task obtaining the highest accuracy and agreement among the participants. We show how a simple evolutionary optimiser may be used to improve the performance by reweighting the importance of annotators.","PeriodicalId":106191,"journal":{"name":"2013 13th UK Workshop on Computational Intelligence (UKCI)","volume":"243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122344026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Large-scale optimization: Are co-operative co-evolution and fitness inheritance additive? 大规模优化:合作、共同进化和适应度遗传是相加的吗?

2013 13th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2013-10-31 DOI: 10.1109/UKCI.2013.6651294

A. Hameed, D. Corne, David Morgan, A. Waldock

{"title":"Large-scale optimization: Are co-operative co-evolution and fitness inheritance additive?","authors":"A. Hameed, D. Corne, David Morgan, A. Waldock","doi":"10.1109/UKCI.2013.6651294","DOIUrl":"https://doi.org/10.1109/UKCI.2013.6651294","url":null,"abstract":"Large-scale optimization - here referring mainly to problems with many design parameters - remains a serious challenge for optimization algorithms. When the problem at hand does not succumb to analytical treatment (an overwhelmingly commonplace situation), the engineering and adaptation of stochastic black box optimization methods tends to be a favoured approach, particularly the use of Evolutionary Algorithms (EAs). In this context, many approaches are currently under investigation for accelerating performance on large-scale problems, and we focus on two of those in this paper. The first is co-operative co-evolution (CC), where the strategy is to successively optimize only subsets of the design parameters at a time, keeping the remainder fixed, with an organized approach to managing and reconciling these `subspace' optimizations. The second is fitness inheritance (FI), which is essentially a very simple surrogate model strategy, in which, with some probability, the fitness of a solution is simply guessed to be a simple function of the fitnesses of that solution's `parents'. Both CC and FI have been found successful on nontrivial and multiple test cases, and they use fundamentally distinct strategies. In this article we explore the extent to which employing both of these strategies at once provides additional benefit. Based on experiments with 50D-1000D variants of four test functions, we find `CCEA-FI' to be highly effective, especially when a random grouping scheme is used in the CC component.","PeriodicalId":106191,"journal":{"name":"2013 13th UK Workshop on Computational Intelligence (UKCI)","volume":"730 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113999255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Stepwise modelling of biochemical pathways based on qualitative model learning 基于定性模型学习的生化途径逐步建模

2013 13th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2013-10-31 DOI: 10.1109/UKCI.2013.6651284

Zujian Wu, Wei Pang, G. Coghill

{"title":"Stepwise modelling of biochemical pathways based on qualitative model learning","authors":"Zujian Wu, Wei Pang, G. Coghill","doi":"10.1109/UKCI.2013.6651284","DOIUrl":"https://doi.org/10.1109/UKCI.2013.6651284","url":null,"abstract":"Modelling of biochemical pathways in a computational way has received considerable attention over the last decade from biochemistry, computing sciences, and mathematics. In this paper we present an approach to evolutionarily stepwise constructing models of biochemical pathways by a qualitative model learning methodology. Given a set of reactants involved in a target biochemical pathway, atomic components can be generated and preserved in a components library for further model composition. These synthetic components are then reused to compose models which are qualitatively evaluated by referring to experimental qualitative states of the given reactants. Simulation results show that our stepwise evolutionary qualitative model learning approach can learn the relationships among reactants in biochemical pathway, by exploring topology space of alternative models. In addition, synthetic biochemical complex can be obtained as hidden reactants in composed models. The inferred hidden reactants and topologies of the synthetic models can be further investigated by biologists in experimental environment for understanding biological principles.","PeriodicalId":106191,"journal":{"name":"2013 13th UK Workshop on Computational Intelligence (UKCI)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121612253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Towards an autonomous resilience strategy the implementation of a self evolving rate limiter 实现自进化速率限制器的自主弹性策略

2013 13th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2013-10-31 DOI: 10.1109/UKCI.2013.6651320

Azman Ali, D. Hutchison, P. Angelov, Paul Smith

{"title":"Towards an autonomous resilience strategy the implementation of a self evolving rate limiter","authors":"Azman Ali, D. Hutchison, P. Angelov, Paul Smith","doi":"10.1109/UKCI.2013.6651320","DOIUrl":"https://doi.org/10.1109/UKCI.2013.6651320","url":null,"abstract":"Distributed Denial of Service (DDoS) attacks on network infrastructure are one of the major challenges facing network service providers. Despite the recent rise of low-volume application-level attacks, volume-based DDoS attacks still dominate, with peak traffic rates of 80Gbps being observed recently. This prompts the need for more efficient ways to deal with them. Meanwhile, service providers are struggling to acquire the right technology, resources and expertise to offer more resilient and reliable services. One of the solutions to help address this issue is to adopt an autonomous resilience strategy that systematically coordinates resilience related activities such as detecting and mitigating attacks. In this paper, we study an implementation of an autonomous traffic rate limiter - a function that can be used to mitigate DDoS attacks - that capitalises on the AnYa algorithm, an autonomous learning systems (ALS) algorithm that provides advanced features that are crucial to support an autonomous resilience strategy. These features include self-structuring and support for online learning. In our study, we experimentally show how remediation and recovery processes can be realized autonomously, in response to changes in the operational policy.","PeriodicalId":106191,"journal":{"name":"2013 13th UK Workshop on Computational Intelligence (UKCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129564364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Face clustering in videos: GMM-based hierarchical clustering using Spatio-Temporal data 视频中的人脸聚类:基于gmm的时空数据分层聚类

2013 13th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2013-10-31 DOI: 10.1109/UKCI.2013.6651316

S. Kayal

{"title":"Face clustering in videos: GMM-based hierarchical clustering using Spatio-Temporal data","authors":"S. Kayal","doi":"10.1109/UKCI.2013.6651316","DOIUrl":"https://doi.org/10.1109/UKCI.2013.6651316","url":null,"abstract":"In recent years, an increase in multimedia data generation and efficient forms of storage have given rise to needs like quick browsing, efficient summarization and techniques for information retrieval. Face Clustering, together with other technologies such as speech recognition, can effectively solve these problems. Applications such as video indexing, major cast detection and video summarization greatly benefit from the development of accurate face clustering algorithms. Since videos represent a temporally ordered collection of faces, it is only natural to use the knowledge of the temporal ordering of these faces, in conjunction with the spatial features extracted from them, to obtain optimal clusterings. This paper is aimed at developing a novel clustering algorithm, by modifying the highly successful hierarchical agglomerative clustering (HAC) process, so that it includes an effective initialization mechanism, via an initial temporal clustering and Gaussian Mixture Model based cluster splitting, and introduces a temporal aspect during cluster combination, in addition to the spatial distances. Experiments show that it significantly outperforms HAC while being equally flexible.","PeriodicalId":106191,"journal":{"name":"2013 13th UK Workshop on Computational Intelligence (UKCI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121516340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Comparison of crisp systems and fuzzy systems in agent-based simulation: A case study of soccer penalties 基于agent的仿真中清晰系统与模糊系统的比较——以足球判罚为例

2013 13th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2013-10-31 DOI: 10.1109/UKCI.2013.6651287

T. Vu, Peer-Olaf Siebers, Christian Wagner

{"title":"Comparison of crisp systems and fuzzy systems in agent-based simulation: A case study of soccer penalties","authors":"T. Vu, Peer-Olaf Siebers, Christian Wagner","doi":"10.1109/UKCI.2013.6651287","DOIUrl":"https://doi.org/10.1109/UKCI.2013.6651287","url":null,"abstract":"The Belief-Desire-Intention (BDI) software model is an example of a reasoning architecture for a bounded rational software agent. In our research we plan to expand the application of the BDI software model to the area of simulating human behaviour in social and socio-technical systems. To this effect, in this paper we explore the differences in using a classical crisp rule-based approach and a fuzzy rule-based approach for the reasoning within the BDI system. As a test case we have chosen a football penalty shootout. We have kept the case study example deliberately simple so that we can focus on the effects the different BDI implementations have on the decisions made. Our experiments highlight that the crisp system can result in unwanted “preferred” actions because of sudden leaps or drops between different ranges of decision variables, while the fuzzy system results have smoother transitions which results in more consistent decisions. The behaviour, as showcased in this simple context, underlines that a change from crisp to fuzzy rule based systems as the underlying reasoning model in BDI systems can provide the path to a superior approach for the simulation of human behaviour, which we will explore further in the future.","PeriodicalId":106191,"journal":{"name":"2013 13th UK Workshop on Computational Intelligence (UKCI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115559573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Novel hybrid bacterial foraging and spiral dynamics algorithms 新型混合细菌觅食和螺旋动力学算法

2013 13th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2013-10-31 DOI: 10.1109/UKCI.2013.6651306

A. Nasir, M. Tokhi, N. Ghani

{"title":"Novel hybrid bacterial foraging and spiral dynamics algorithms","authors":"A. Nasir, M. Tokhi, N. Ghani","doi":"10.1109/UKCI.2013.6651306","DOIUrl":"https://doi.org/10.1109/UKCI.2013.6651306","url":null,"abstract":"This paper presents three novel hybrid optimization algorithms based on bacterial foraging and spiral dynamics algorithms and their application to modelling of flexible maneuvering systems. Hybrid bacteria-chemotaxis spiral-dynamics algorithm is a combination of chemotaxis strategy in bacterial foraging algorithm and linear adaptive spiral dynamics algorithm. Chemotactic behaviour of bacteria is a good strategy for fast exploration if large value of step size is defined in the motion. However, this results in oscillation in the search process and bacteria cannot reach optimum fitness accuracy in the final solution. On the contrary, spiral dynamics provides good exploitation strategy due to its dynamic step size. However, it suffers from getting trapped at local optima due to poor exploration in the diversification phase. Employing the chemotaxis and spiral dynamics strategies at the initial and final stages respectively will thus balance the exploration and exploitation. Hybrid spiral-bacterial foraging algorithm and hybrid chemotaxis-spiral algorithm, on the other hand are developed based on adaptation of spiral dynamics model into chemotaxis phase of bacterial foraging with the aim to guide bacteria movement globally. The proposed algorithms are used to optimize parameters of a linear parametric model of a flexible robot manipulator system. The performances of the proposed hybrid algorithms are presented in comparison to their predecessor algorithms in terms of fitness accuracy, time-domain and frequency-domain responses of the models. The results show that the proposed algorithms achieve better performance.","PeriodicalId":106191,"journal":{"name":"2013 13th UK Workshop on Computational Intelligence (UKCI)","volume":"295 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116591540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

Minkowski compactness measure 闵可夫斯基紧度测度

2013 13th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2013-10-31 DOI: 10.1109/UKCI.2013.6651288

C. Martinez-Ortiz, R. Everson

引用次数: 3

Efficient feature selection using a self-adjusting harmony search algorithm 采用自调整和声搜索算法的高效特征选择

2013 13th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2013-10-31 DOI: 10.1109/UKCI.2013.6651302

Ling Zheng, R. Diao, Q. Shen

引用次数: 9

Evolving neural networks using ant colony optimization with pheromone trail limits 基于信息素轨迹限制的蚁群优化进化神经网络

2013 13th UK Workshop on Computational Intelligence (UKCI) Pub Date : 2013-10-31 DOI: 10.1109/UKCI.2013.6651282

Michalis Mavrovouniotis, Shengxiang Yang

引用次数: 22