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Kirsty Kitto

Senior Lecturer, Connected Intelligence Centre
THEORETICAL PHYSICS, PHILOSOPHY, Theoretical Physics, COMPUTER SCIENCE, PhD (Physics)
 
Can supervise: Yes

Books

Atmanspacher, H., Bergomi, C., Filk, T. & Kitto, K. 2015, Preface.
Atmanspacher, H., Haven, E., Kitto, K. & Raine, D. 2014, Preface.

Chapters

Kitto, K. 2008, 'Process physics: Quantum theories as models of complexity' in Physics of Emergence and Organization, pp. 77-88.
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© 2008 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. Originally based upon a pregeometric model of the Universe, Process Physics has now been formulated as far more general modeling paradigm that is capable of generating complex emergent behavior. This article discusses the original re- lational model of Process Physics and the emergent hierarchical structure that it generates, linking the reason for this emergence to the historical basis of the model in quantum field theory. This historical connection is used to motivate a new interpretation of the general class of quantum theories as providing mod- els of certain aspects of complex behavior. A summary of this new realistic interpretation of quantum theory is presented and some applications of this viewpoint to the description of complex emergent behavior are sketched out.

Conferences

Clow, D., Ferguson, R., Kitto, K., Cho, Y.S., Sharkey, M. & Aguerrebere, C. 2017, 'Beyond failure: The 2nd LAK Failathon', ACM International Conference Proceeding Series, pp. 504-505.
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© 2017 ACM. The 2n LAK Failathon will build on the successful event in 2016 and extend the workshop beyond discussing individual experiences of failure to exploring how the field can improve, particularly regarding the creation and use of evidence. Failure in research is an increasingly hot topic, with high-profile crises of confidence in the published research literature in medicine and psychology. Among the major factors in this research crisis are the many incentives to report and publish only positive findings. These incentives prevent the field in general from learning from negative findings, and almost entirely preclude the publication of mistakes and errors. Thus providing an alternative forum for practitioners and researchers to learn from each other's failures can be very productive. The first LAK Failathon, held in 2016, provided just such an opportunity for researchers and practitioners to share their failures and negative findings in a lower-stakes environment, to help participants learn from each other's mistakes. It was very successful, and there was strong support for running it as an annual event. This workshop will build on that success, with twin objectives to provide an environment for individuals to learn from each other's failures, and also to co-develop plans for how we as a field can better build and deploy our evidence base.
Cross, S., Waters, Z., Kitto, K. & Zuccon, G. 2017, 'Classifying help seeking behaviour in online communities', ACM International Conference Proceeding Series, pp. 419-423.
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© 2017 ACM. While help seeking has been extensively studied using self report survey data and models, there is a lack of content analysis techniques that can be directly applied to classify help seeking behaviour. In this preliminary work we propose a coding scheme which is then applied to an open dataset that we have created by carefully selecting sub groups from two popular discussion sites (Reddit and StackExchange). We then explore the possibility for automatically classifying help seeking behaviour using machine learning models. A preliminary model provides good initial results, suggesting that it may indeed be possible to construct student support systems that build off of an accurate classifier.
Clow, D., Ferguson, R., Kitto, K., Cho, Y.S., Sharkey, M. & Aguerrebere, C. 2017, 'Beyond failure: The 2nd LAK Failathon poster', ACM International Conference Proceeding Series, pp. 540-541.
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© 2017 ACM. This poster will be a chance for a wider LAK audience to engage with the 2 nd LAK Failathon workshop. Both of these will build on the successful Failathon event in 2016 and extend beyond discussing individual experiences of failure to exploring how the field can improve, particularly regarding the creation and use of evidence. Failure in research is an increasingly hot topic, with high-profile crises of confidence in the published research literature in medicine and psychology. Among the major factors in this research crisis are the many incentives to report and publish only positive findings. These incentives prevent the field in general from learning from negative findings, and almost entirely preclude the publication of mistakes and errors. Thus providing an alternative forum for practitioners and researchers to learn from each other's failures can be very productive. The first LAK Failathon, held in 2016, provided just such an opportunity for researchers and practitioners to share their failures and negative findings in a lower-stakes environment, to help participants learn from each other's mistakes. It was very successful, and there was strong support for running it as an annual event. The 2n LAK Failathon workshop will build on that success, with twin objectives to provide an environment for individuals to learn from each other's failures, and also to co-develop plans for how we as a field can better build and deploy our evidence base. This poster is an opportunity for wider feedback on the plans developed in the workshop, with interactive use of sticky notes to add new ideas and coloured dots to illustrate prioritisation. This broadens the participant base in this important work, which should improve the quality of the plans and the commitment of the community to delivering them.
Cooper, A., Berg, A., Sclater, N., Dorey-Elias, T. & Kitto, K. 2017, 'LAK17 Hackathon - Getting the right information to the right people so they can take the right action', ACM International Conference Proceeding Series, pp. 514-515.
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© 2017 ACM. The hackathon is intended to be a practical hands-on workshop involving participants from academia and commercial organizations with both technical and practitioner expertise. It will consider the outstanding challenge of visualizations which are effective for the intended audience: informing action, not likely to be misinterpreted, and embodying contextual appropriacy, etc. It will surface particular issues as workshop challenges and explore responses to these challenges as visualizations resting upon interoperability standards and API-oriented open architectures.
Kitto, K., Bakharia, A., Lupton, M., Mallet, D., Banks, J., Bruza, P., Pardo, A., Shum, S.B., Dawsony, S., Gaševícy, D., Siemensg, G. & Lynch, G. 2016, 'The connected learning analytics toolkit', ACM International Conference Proceeding Series, International Conference on Learning Analytics & Knowledge (LAK), Association of Computing Machinery, Edinburgh, United Kingdom, pp. 548-549.
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© 2016 Copyright held by the owner/author(s).This demonstration introduces the Connected Learning An- Alytics (CLA) Toolkit. The CLA toolkit harvests data about student participation in specified learning activities across standard social media environments, and presents information about the nature and quality of the learning interactions.
Martinez-Maldonado, R., Suthers, D., Aljohani, N.R., Hernandez-Leo, D., Kitto, K., Pardo, A., Charleer, S. & Ogata, H. 2016, 'Cross-LAK: Learning analytics across physical and digital spaces', ACM International Conference Proceeding Series, pp. 486-487.
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© 2016 Copyright held by the owner/author(s). It is of high relevance to the LAK community to explore blended learning scenarios where students can interact at diverse digital and physical learning spaces. This workshop aims to gather the sub-community of LAK researchers, learning scientists and researchers from other communities, interested in ubiquitous, mobile and/or faceto- face learning analytics. An overarching concern is how to integrate and coordinate learning analytics to provide continued support to learning across digital and physical spaces. The goals of the workshop are to share approaches and identify a set of guidelines to design and connect Learning Analytics solutions according to the pedagogical needs and contextual constraints to provide support across digital and physical learning spaces.
Bakharia, A., Kitto, K., Pardo, A., Gaševíc, D. & Dawson, S. 2016, 'Recipe for Success - Lessons learnt from using xAPI within the connected learning analytics toolkit', ACM International Conference Proceeding Series, pp. 378-382.
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© 2016 ACM. An ongoing challenge for Learning Analytics research has been the scalable derivation of user interaction data from multiple technologies. The complexities associated with this challenge are increasing as educators embrace an ever grow- ing number of social and content-related technologies. The Experience API (xAPI) alongside the development of user specific record stores has been touted as a means to ad- dress this challenge, but a number of subtle considerations must be made when using xAPI in Learning Analytics. This paper provides a general overview to the complexities and challenges of using xAPI in a general systemic analytics solution - called the Connected Learning Analytics (CLA) toolkit. The importance of design is emphasised, as is the notion of common vocabularies and xAPI Recipes. Early decisions about vocabularies and structural relationships be- Tween statements can serve to either facilitate or handicap later analytics solutions. The CLA toolkit case study pro- vides us with a way of examining both the strengths and the weaknesses of the current xAPI specification, and we con- clude with a proposal for how xAPI might be improved by using JSON-LD to formalise Recipes in a machine readable form.
Kovanovíc, V., Joksimovíc, S., Waters, Z., Gaševíc, D., Kitto, K., Hatala, M. & Siemens, G. 2016, 'Towards automated content analysis of discussion transcripts: A cognitive presence case', ACM International Conference Proceeding Series, International Conference on Learning Analytics & Knowledge, Association for Computing Machinery (ACM), Edinburgh, Scotland, pp. 15-24.
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In this paper, we present the results of an exploratory study that examined the problem of automating content analysis of student online discussion transcripts. We looked at the problem of coding discussion transcripts for the levels of cognitive presence, one of the three main constructs in the Community of Inquiry (CoI) model of distance education. Using Coh-Metrix and LIWC features, together with a set of custom features developed to capture discussion context, we developed a random forest classification system that achieved 70.3% classification accuracy and 0.63 Cohen's kappa, which is significantly higher than values reported in the previous studies. Besides improvement in classification accuracy, the developed system is also less sensitive to overfitting as it uses only 205 classification features, which is around 100 times less features than in similar systems based on bag-of-words features. We also provide an overview of the classification features most indicative of the different phases of cognitive presence that gives an additional insights into the nature of cognitive presence learning cycle. Overall, our results show great potential of the proposed approach, with an added benefit of providing further characterization of the cognitive presence coding scheme.
Kitto, K. & Widdows, D. 2016, 'Ideologies and their points of view', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Quantum Interaction, Springer, San Francisco, California, United States, pp. 216-227.
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It is well known that different arguments appeal to different people. We all process information in ways that are adapted to be consistent with our underlying ideologies. These ideologies can sometimes be framed in terms of particular axes or dimensions, which makes it possible to represent some aspects of an ideology as a region in the kind of vector space that is typical of many generalised quantum models. Such models can then be used to explain and predict, in broad strokes, whether a particular argument or proposal is likely to appeal to an individual with a particular ideology. The choice of suitable arguments to bring about desired actions is traditionally part of the art or science of rhetoric, and today's highly polarised society means that this skill is becoming more important than ever. This paper presents a basic model for understanding how different goals will appeal to people with different ideologies, and thus how different rhetorical positions can be adopted to promote the same desired outcome. As an example, we consider different narratives and hence actions with respect to the environment and climate change, an important but currently highly controversial topic.
Aliakbarzadeh, M. & Kitto, K. 2016, 'Applying POVM to model non-orthogonality in quantum cognition', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Quantum Interaction, Springer, San Francisco, California, United States, pp. 284-293.
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Much of the work currently occurring in the field of Quantum Interaction (QI) relies upon Projective Measurement. This is perhaps not optimal, cognitive states are not nearly as well behaved as standard quantum mechanical systems; they exhibit violations of repeatability, and the operators that we use to describe measurements do not appear to be naturally orthogonal in cognitive systems. Here we attempt to map the formalism of Positive Operator Valued Measure (POVM) theory into the domain of semantic memory, showing how it might be used to construct Bell-type inequalities.
Gibson, A.P. & Kitto, K. 2015, 'Analysing reflective text for learning analytics : an approach using anomaly recontextualisation', Proceedings of the Fifth International Conference on Learning Analytics And Knowledge, Fifth International Conference on Learning Analytics And Knowledge, ACM, Poughkeepsie, NY, USA, pp. 275-279.
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Reflective writing is an important learning task to help foster reflective practice, but even when assessed it is rarely analysed or critically reviewed due to its subjective and affective nature. We propose a process for capturing subjective and affective analytics based on the identification and recontextualisation of anomalous features within reflective text. We evaluate 2 human supervised trials of the process, and so demonstrate the potential for an automated Anomaly Recontextualisation process for Learning Analytics.
Waters, Z., Kovanovi, V., Kitto, K. & Gaševi, D. 2015, 'Structure matters: Adoption of structured classification approach in the context of cognitive presence classification', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 227-238.
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© Springer International Publishing Switzerland 2015. Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods–such as the Community of Inquiry framework–rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of online discussions for the classification of 'cognitive presence–the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.
Kitto, K., Cross, S., Waters, Z. & Lupton, M. 2015, 'Learning analytics beyond the LMS: The connected learning analytics toolkit', ACM International Conference Proceeding Series, pp. 11-15.
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We present a Connected Learning Analytics (CLA) toolkit, which enables data to be extracted from social media and imported into a Learning Record Store (LRS), as defined by the new xAPI standard. A number of implementation issues are discussed, and a mapping that will enable the consistent storage and then analysis of xAPI verb/object/activity statements across different social media and online environments is introduced. A set of example learning activities are proposed, each facilitated by the Learning Analytics beyond the LMS that the toolkit enables.
Atmanspacher, H., Bergomi, C., Filk, T. & Kitto, K. 2015, 'Quantum Interaction: 8th International Conference, QI 2014 Filzbach, Switzerland, June 30 - July 3, 2014 Revised Selected Papers', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
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Kitto, K., Sonnenburg, L., Boschetti, F. & Walker, I. 2015, 'Modelling attitudes to climate change — an order effect and a test between alternatives', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 119-131.
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© Springer International Publishing Switzerland 2015. Quantum-like models can be fruitfully used to model attitude change in a social context. Next steps require data, and higher dimensional models. Here, we discuss an exploratory study that demonstrates an order effect when three question sets about Climate Beliefs, Political Affiliation and Attitudes Towards Science are presented in different orders within a larger study of n = 533 subjects. A quantum-like model seems possible, and we propose a new experiment which could be used to test between three possible models for this scenario.
Gibson, A., Kitto, K. & Willis, J. 2014, 'A cognitive processing framework for learning analytics', ACM International Conference Proceeding Series, pp. 212-216.
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Incorporating a learner's level of cognitive processing into Learning Analytics presents opportunities for obtaining rich data on the learning process. We propose a framework called COPA that provides a basis for mapping levels of cognitive operation into a learning analytics system. We utilise Bloom's taxonomy, a theoretically respected conceptualisation of cognitive processing, and apply it in a flexible structure that can be implemented incrementally and with varying degree of complexity within an educational organisation. We outline how the framework is applied, and its key benefits and limitations. Finally, we apply COPA to a University undergraduate unit, and demonstrate its utility in identifying key missing elements in the structure of the course. Copyright © 2014 by the Association for Computing Machinery, Inc.
Darányi, S., Wittek, P. & Kitto, K. 2014, 'The sphynx's new riddle: How to relate the canonical formula of myth to quantum interaction', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 47-58.
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We introduce Claude Lévi Strauss' canonical formula (CF), an attempt to rigorously formalise the general narrative structure of myth. This formula utilises the Klein group as its basis, but a recent work draws attention to its natural quaternion form, which opens up the possibility that it may require a quantum inspired interpretation. We present the CF in a form that can be understood by a non-anthropological audience, using the formalisation of a key myth (that of Adonis) to draw attention to its mathematical structure. The future potential formalisation of mythological structure within a quantum inspired framework is proposed and discussed, with a probabilistic interpretation further generalising the formula. © 2014 Springer-Verlag Berlin Heidelberg.
Galea, D., Bruza, P., Kitto, K. & Nelson, D. 2012, 'Modelling word activation in semantic networks: Three scaled entanglement models compared', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 172-183.
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Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. Previous research assumed a quantum-like model in which the semantic network was modelled as entangled qubits, however the level of activation was clearly being overestimated. This paper explores three variations of this model, each of which are distinguished by a scaling factor designed to compensate the overestimation. © 2012 Springer-Verlag.
Kitto, K., Boschetti, F. & Bruza, P. 2012, 'The quantum inspired modelling of changing attitudes and self-organising societies', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 1-12.
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We utilise the quantum decision models, now well-developed in the QI community, to create a higher order social decision making model. A simple Agent Based Model (ABM) of a society of agents with changing attitudes towards a social issue is presented, where the private attitudes of individuals in the system are represented using a geometric structure inspired by quantum theory. We track the changing attitudes of the members of that society, and their resulting propensities to act, or not, in a given social context. A number of new issues surrounding this "scaling up" of quantum decision theories are discussed, as well as new directions and opportunities. © 2012 Springer-Verlag.
Kitto, K., Bruza, P. & Gabora, L. 2012, 'A quantum information retrieval approach to memory', Proceedings of the International Joint Conference on Neural Networks.
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As computers approach the physical limits of information storable in memory, new methods will be needed to further improve information storage and retrieval. We propose a quantum inspired vector based approach, which offers a contextually dependent mapping from the subsymbolic to the symbolic representations of information. If implemented computationally, this approach would provide exceptionally high density of information storage, without the traditionally required physical increase in storage capacity. The approach is inspired by the structure of human memory and incorporates elements of Grdenfors' Conceptual Space approach and Humphreys et al.'s matrix model of memory. © 2012 IEEE.
Kitto, K., Boschetti, F. & Bruza, P. 2011, 'The geometric modelling of social frames and contexts', MODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty, pp. 2975-2981.
How do humans respond to their social context? This question is becoming increasingly urgent in a society where democracy requires that the citizens of a country help to decide upon its policy directions, and yet those citizens frequently have very little knowledge of the complex issues that these policies seek to address. Frequently, we find that humans make their decisions more with reference to their social setting, than to the arguments of scientists, academics, and policy makers. It is broadly anticipated that the agent based modelling (ABM) of human behaviour will make it possible to treat such social effects, but we take the position here that a more sophisticated treatment of context will be required in many such models. While notions such as historical context (where the past history of an agent might affect its later actions) and situational context (where the agent will choose a different action in a different situation) abound in ABM scenarios, we will discuss a case of a potentially changing context, where social effects can have a strong influence upon the perceptions of a group of subjects. In particular, we shall discuss a recently reported case where a biased worm in an election debate led to significant distortions in the reports given by participants as to who won the debate (Davis et al., 2011). Thus, participants in a different social context drew different conclusions about the perceived winner of the same debate, with associated significant differences among the two groups as to who they would vote for in the coming election. We extend this example to the problem of modelling the likely electoral responses of agents in the context of the climate change debate, and discuss the notion of interference between related questions that might be asked of an agent in a social simulation that was intended to simulate their likely responses. A modelling technology which could account for such strong social contextual effects would benefit regulatory b...
Galea, D., Bruza, P., Kitto, K., Nelson, D. & McEvoy, C. 2011, 'Modelling the acitivation of words in human memory: The spreading activation, spooky-activation-at-a-distance and the entanglement models compared', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 149-160.
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Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. The spreading activation, spooky-action-at-a-distance and entanglement models have all been used to model the activation of a word. Recently a hypothesis was put forward that the mean activation levels of the respective models are as follows: Spreading Entanglment Spooking-action-at-a-distance This article investigates this hypothesis by means of a substantial empirical analysis of each model using the University of South Florida word association, rhyme and word norms. © 2011 Springer-Verlag.
Aerts, S., Kitto, K. & Sitbon, L. 2011, 'Similarity metrics within a point of view', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 13-24.
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Vector space based approaches to natural language processing are contrasted with human similarity judgements to show the manner in which human subjects fail to produce data which satisfies all requirements for a metric space. This result would constrains the validity and applicability vector space based (and hence also quantum inspired) approaches to the modelling of cognitive processes. This paper proposes a resolution to this problem, by arguing that pairs of words imply a context which in turn induces a point of view, so allowing a subject to estimate semantic similarity. Context is here introduced as a point of view vector (POVV) and the expected similarity is derived as a measure over the POVV's. Different pairs of words will invoke different contexts and different POVV's. We illustrate the proposal on a few triples of words and outline further research. © 2011 Springer-Verlag.
Bruza, P., Iqbal, A. & Kitto, K. 2010, 'The role of non-factorizability in determining "pseudo-classical" non-separability', AAAI Fall Symposium - Technical Report, pp. 26-31.
This article introduces a "pseudo classical" notion of modelling non-separability. This form of non-separability can be viewed as lying between separability and quantum-like non-separability. Non-separability is formalized in terms of the non-factorizabilty of the underlying joint probability distribution. A decision criterium for determining the non-factorizability of the joint distribution is related to determining the rank of a matrix as well as another approach based on the chi-square-goodness-of-fit test. This pseudo-classical notion of non-separability is discussed in terms of quantum games and concept combinations in human cognition. Copyright ©2010, Association for the Advancement of Artificial Intelligence. All rights reserved.
Kitto, K., Ramm, B., Bruza, P. & Sitbon, L. 2010, 'Testing for the non-separability of bi-ambiguous compounds', AAAI Fall Symposium - Technical Report, pp. 62-69.
Separability is a concept that is very difficult to define, and yet much of our scientific method is implicitly based upon the assumption that systems can sensibly be reduced to a set of interacting components. This paper examines the notion of separability in the creation of bi-ambiguous compounds that is based upon the CHSH and CH inequalities. It reports results of an experiment showing that violations of the CHSH and CH inequality can occur in human conceptual combination. Copyright © 2010, Association for the Advancement of Artificial Intelligence. All rights reserved.
Flender, C., Kitto, K. & Bruza, P. 2009, 'Beyond ontology in information systems', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 276-288.
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Information systems are socio-technical systems. Their design, analysis and implementation requires appropriate languages for representing social and technical concepts. However, many symbolic modelling approaches fall into the trap of underemphasizing social aspects of information systems. This often leads to an inability of onto- logical models to incorporate effects such as contextual dependence and emergence. Moreover, as designers take the perspective of people living with and alongside the information system to be modelled social interaction becomes a primary concern. Ontologies are too prescriptive and do not account properly for social concepts. Based on State-Context- Property (SCoP) systems we propose a quantum-inspired approach for modelling information systems. © Springer-Verlag Berlin Heidelberg 2009.
Kitto, K., Bruza, P. & Sitbon, L. 2009, 'Generalising unitary time evolution', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 17-28.
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In this third Quantum Interaction (QI) meeting it is time to examine our failures. One of the weakest elements of QI as a field, arises in its continuing lack of models displaying proper evolutionary dynamics. This paper presents an overview of the modern generalised approach to the derivation of time evolution equations in physics, showing how the notion of symmetry is essential to the extraction of operators in quantum theory. The form that symmetry might take in non-physical models is explored, with a number of viable avenues identified. © Springer-Verlag Berlin Heidelberg 2009.
Bruza, P., Kitto, K., Nelson, D. & McEvoy, C. 2009, 'Extracting spooky-activation-at-a-distance from considerations of entanglement', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 71-83.
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Following an early claim by Nelson & McEvoy suggesting that word associations can display 'spooky action at a distance behaviour', a serious investigation of the potentially quantum nature of such associations is currently underway. This paper presents a simple quantum model of a word association system. It is shown that a quantum model of word entanglement can recover aspects of both the Spreading Activation model and the Spooky model of word association experiments. © Springer-Verlag Berlin Heidelberg 2009.
Flender, C., Kitto, K. & Bruza, P. 2009, 'Nonseparability of shared intentionality', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 211-224.
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According to recent studies in developmental psychology and neuroscience, symbolic language is essentially intersubjective. Empatheti- cally relating to others renders possible the acquisition of linguistic constructs. Intersubjectivity develops in early ontogenetic life when interactions between mother and infant mutually shape their relatedness. Empirical findings suggest that the shared attention and intention involved in those interactions is sustained as it becomes internalized and embodied. Symbolic language is derivative and emerges from shared intentional- ity. In this paper, we present a formalization of shared intentionality based upon a quantum approach. From a phenomenological viewpoint, we investigate the nonseparable, dynamic and sustainable nature of social cognition and evaluate the appropriateness of quantum interaction for modelling intersubjectivity. © Springer-Verlag Berlin Heidelberg 2009.

Journal articles

Bruza, P.D., Kitto, K., Ramm, B.J. & Sitbon, L. 2015, 'A probabilistic framework for analysing the compositionality of conceptual combinations', Journal of Mathematical Psychology, vol. 67, pp. 26-38.
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© 2015. Conceptual combination performs a fundamental role in creating the broad range of compound phrases utilised in everyday language. While the systematicity and productivity of language provide a strong argument in favour of assuming compositionality, this very assumption is still regularly questioned in both cognitive science and philosophy. This article provides a novel probabilistic framework for assessing whether the semantics of conceptual combinations are compositional, and so can be considered as a function of the semantics of the constituent concepts, or not. Rather than adjudicating between different grades of compositionality, the framework presented here contributes formal methods for determining a clear dividing line between compositional and non-compositional semantics. Compositionality is equated with a joint probability distribution modelling how the constituent concepts in the combination are interpreted. Marginal selectivity is emphasised as a pivotal probabilistic constraint for the application of the Bell/CH and CHSH systems of inequalities (referred to collectively as Bell-type). Non-compositionality is then equated with either a failure of marginal selectivity, or, in the presence of marginal selectivity, with a violation of Bell-type inequalities. In both non-compositional scenarios, the conceptual combination cannot be modelled using a joint probability distribution with variables corresponding to the interpretation of the individual concepts. The framework is demonstrated by applying it to an empirical scenario of twenty-four non-lexicalised conceptual combinations.
Kitto, K. & Kortschak, R.D. 2013, 'Contextual models and the non-Newtonian paradigm.', Prog Biophys Mol Biol, vol. 113, no. 1, pp. 97-107.
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Biological systems exhibit a wide range of contextual effects, and this often makes it difficult to construct valid mathematical models of their behaviour. In particular, mathematical paradigms built upon the successes of Newtonian physics make assumptions about the nature of biological systems that are unlikely to hold true. After discussing two of the key assumptions underlying the Newtonian paradigm, we discuss two key aspects of the formalism that extended it, Quantum Theory (QT). We draw attention to the similarities between biological and quantum systems, motivating the development of a similar formalism that can be applied to the modelling of biological processes.
Nelson, D.L., Kitto, K., Galea, D., McEvoy, C.L. & Bruza, P.D. 2013, 'How activation, entanglement, and searching a semantic network contribute to event memory.', Mem Cognit, vol. 41, no. 6, pp. 797-819.
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Free-association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long-lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist-cuing, primed free-association, intralist-cuing, and single-item recognition tasks. The findings also show that when a related word is presented in order to cue the recall of a studied word, the cue activates the target in an array of related words that distract and reduce the probability of the target's selection. The activation of the semantic network produces priming benefits during encoding, and search costs during retrieval. In extralist cuing, recall is a negative function of cue-to-distractor strength, and a positive function of neighborhood density, cue-to-target strength, and target-to-cue strength. We show how these four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks, indicating that the contribution of the semantic network varies with the context provided by the task. Finally, we evaluate spreading-activation and quantum-like entanglement explanations for the priming effects produced by neighborhood density.
Kitto, K. & Boschetti, F. 2013, 'Attitudes, ideologies and self-organization: Information load minimization in multi-agent decision making', Advances in Complex Systems, vol. 16, no. 2-3.
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Sophisticated models of human social behavior are fast becoming highly desirable in an increasingly complex and interrelated world. Here, we propose that rather than taking established theories from the physical sciences and naively mapping them into the social world, the advanced concepts and theories of social psychology should be taken as a starting point, and used to develop a new modeling methodology. In order to illustrate how such an approach might be carried out, we attempt to model the low elaboration attitude changes of a society of agents in an evolving social context. We propose a geometric model of an agent in context, where individual agent attitudes are seen to self-organize to form ideologies, which then serve to guide further agent-based attitude changes. A computational implementation of the model is shown to exhibit a number of interesting phenomena, including a tendency for a measure of the entropy in the system to decrease, and a potential for externally guiding a population of agents toward a new desired ideology. © World Scientific Publishing Company.
Kitto, K. & Bruza, P. 2012, 'Non-compositional concepts and quantum tests', AIP Conference Proceedings, vol. 1424, pp. 458-462.
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Compositionality is a frequently made assumption in linguistics, and yet many human subjects reveal highly non-compositional word associations when confronted with novel concept combinations. This article will show how a non-compositional account of concept combinations can be supplied by modelling them as interacting quantum systems. © 2012 American Institute of Physics.
Bruza, P.D., Kitto, K., Ramm, B., Sitbon, L., Song, D. & Blomberg, S. 2012, 'Quantum-like non-separability of concept combinations, emergent associates and abduction', Logic Journal of the IGPL, vol. 20, no. 2, pp. 445-457.
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Consider the concept combination 'pet human'. In word association experiments, human subjects produce the associate 'slave' in relation to this combination. The striking aspect of this associate is that it is not produced as an associate of 'pet', or 'human' in isolation. In other words, the associate 'slave' seems to be emergent. Such emergent associations sometimes have a creative character and cognitive science is largely silent about how we produce them. Departing from a dimensional model of human conceptual space, this article will explore concept combinations, and will argue that emergent associations are a result of abductive reasoning within conceptual space, that is, below the symbolic level of cognition. A tensor-based approach is used to model concept combinations allowing such combinations to be formalized as interacting quantum systems. Free association norm data is used to motivate the underlying basis of the conceptual space. It is shown by analogy how some concept combinations may behave like quantum-entangled (non-separable) particles. Two methods of analysis were presented for empirically validating the presence of non-separable concept combinations in human cognition. One method is based on quantum theory and another based on comparing a joint (true theoretic) probability distribution with another distribution based on a separability assumption using a chi-square goodness-of-fit test. Although these methods were inconclusive in relation to an empirical study of bi-ambiguous concept combinations, avenues for further refinement of these methods are identified. © The Author 2011. Published by Oxford University Press. All rights reserved.
Kitto, K., Ramm, B., Sitbon, L. & Bruza, P. 2011, 'Quantum Theory Beyond the Physical: Information in Context', Axiomathes, vol. 21, no. 2, pp. 331-345.
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Measures and theories of information abound, but there are few formalised methods for treating the contextuality that can manifest in different information systems. Quantum theory provides one possible formalism for treating information in context. This paper introduces a quantum inspired model of the human mental lexicon. This model is currently being experimentally investigated and we present a preliminary set of pilot data suggesting that concept combinations can indeed behave non-separably. © 2011 Springer Science+Business Media B.V.
Bruza, P., Kitto, K., Nelson, D. & McEvoy, C. 2009, 'Is there something quantum-like about the human mental lexicon?', Journal of Mathematical Psychology, vol. 53, no. 5, pp. 362-377.
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Following an early claim by Nelson and McEvoy suggesting that word associations can display 'spooky action at a distance behaviour', a serious investigation of the potentially quantum nature of such associations is currently underway. In this paper quantum theory is proposed as a framework suitable for modelling the human mental lexicon, specifically the results obtained from both intralist and extralist word association experiments. Some initial models exploring this hypothesis are discussed, and experiments capable of testing these models proposed. © 2009 Elsevier Inc. All rights reserved.
Kitto, K. 2008, 'High end complexity', International Journal of General Systems, vol. 37, no. 6, pp. 689-714.
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Despite the general recognition of complexity as an important concept and decades of work, very little progress has been made in the attempt to define complexity. It is suggested that this is due to the fact that the definition of complex behaviour is itself complex, forming a scale from the simple to the more and more complex. Those systems at the high end of the scale are not at present well modelled, and reasons why this might be the case are presented. The possibility that quantum theories may be able to model such high end complexity is investigated.
Cahill, R.T. & Kitto, K. 2003, 'Michelson-Morley experiments revisited and the cosmic background radiation preferred frame', Apeiron, vol. 10, no. 2, pp. 104-117.
A new information-theoretic physics has given rise to a quantum-foam description of space relative to which absolute motion is meaningful and measurable. In this new physics Michelson interferometers operating in gas mode are capable of revealing absolute motion. We analyse the old results from gas-mode Michelson interferometer experiments which always showed small but significant effects. Analysis of the Illingworth (1927) experimental data, after correcting for the refractive index effect of the helium used, reveals an absolute speed of the Earth of v = 369 ± 123 km/s, while the Miller experiment (1933), after correcting for the refractive index effect of the air, now gives a speed of v = 335 ± 57 km/s, which are in agreement with the speed of v = 365 ± 18 km/s determined from the dipole fit, in 1991, to the NASA COBE satellite Cosmic Background Radiation (CBR) observations. The new physics also implies that vacuum interferometers will give null results, as has been observed many times. These experimental results imply that absolute motion is observable and that there is a preferred foliation of spacetime coinciding with the CBR frame.
Cahill, R., Klinger, C. & Kitto, K. 2000, 'Process physics: Modelling reality as self-organizing information', Physicist, vol. 37, no. 6, p. 191.
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