Goal Legibility and Recognition for Anonymous Multi-Agent Pathfinding Systems:A Graph Theoretical Approach

Goal legibility, one of the dimensions of agent interpretability, has gained significant attention in human-machine interaction research. This thesis explores goal legibility in relation to goal recognition in a multi-agent setting with an observer-in-the-loop. Specifically, it considers an environment where identical agents move from an origin to designated destinations, and an observer monitors their movements, aiming to infer their destinations as quickly as possible. Our approach generates legible paths that minimize overlap while satisfying budget constraints. We also developed a goal recognition framework that maps observation sequences to specific destinations, enabling the observer to infer an agent's goal with minimal (legibility) delay. The legible path planning problem is reformulated as a classical network flow problem for fully observable scenarios, using combinatorial optimization tools to create scalable algorithms. The method adapts efficiently to partially observable settings as well. While effective, these techniques can become computationally demanding. To address this, we introduced initial goal legibility, where the observer begins monitoring agents from their entry point. This variant focuses on inferring destinations by observing initial trajectories. Through mathematical reformulations, our approach computes paths that minimize trajectory overlap, and agents then follow optimal routes. This method is applicable to both fully and partially observable environments. Empirical evaluations demonstrate the scalability and efficiency of our techniques, confirming their practical relevance

Top Friends: Probing Higgs boson associated production with top quarks using the ATLAS detector

The Standard Model (SM) of particle physics represents the leading theoretical framework describing fundamental particles and their interactions. The generation of particle masses is explained via the Brout-Englert-Higgs mechanism, which introduces spontaneous symmetry breaking in the electroweak sector and predicts the existence of a scalar boson, known as the Higgs Boson. The Higgs Boson was experimentally confirmed by both the ATLAS and CMS collaborations at the Large Hadron Collider (LHC), CERN in 2012. The exploration of the Higgs Boson's properties, in particular its interactions with fermions, constitutes a pivotal aspect of the post-Higgs discovery era at the LHC. Among these, measuring Higgs production in association with a pair of top quarks ($t\bar{t}H$) offers a unique window into the Higgs-top-Yukawa coupling, the largest predicted Yukawa coupling in the SM. Precise measurements of $t\bar{t}H$ are required to either validate the SM prediction or highlight deviations hinting at possible new physics. This thesis presents a measurement of the $t\bar{t}H$ production cross-section in the $H\rightarrow b\bar{b}$ decay channel. The analysis is performed using 140~\text{fb}^{-1}}~of proton-proton collision data at a centre of mass energy of $\sqrt{s}=13$ TeV, collected with the ATLAS detector between 2015--2018 at the LHC, corresponding to the full Run 2 dataset. The analysis focuses on events with one or two light charged-leptons in the final state. The development and validation of the profile likelihood fit used to extract the signal cross-section is presented. Neural networks employing attention mechanisms and permutation invariant architectures, known as transformers, perform event classification and reconstruction. Network decisions and potential domain bias levels are studied and presented alongside studies to select the optimal set of observables for the profile likelihood fit. Events in excess of the background-only hypothesis are found, equivalent to an observed (expected) discovery significance of 4.6 (5.4) standard deviations, with a measured cross-section of \sigma_{\ttH} = 411^{+101}_{-92}~\fb = 411 \pm 54~\text{(stat.)}~^{+85}_{-75}~\text{(syst.)} \text{fb}\ ,the most precise individual measurement of $t\bar{t}H$ production to date. The measurement agrees with the SM prediction. Differential cross-section measurements with respect to the Higgs Boson transverse momentum are also performed within the simplified template cross-section framework. The analysis provides critical precision in the high $p_{T}^{H}$ regime for future combination and Effective field theory (EFT) interpretations

Digital CBT for OCD: Perspectives on the therapeutic alliance from adolescents and therapists

Adolescents with obsessive-compulsive disorder (OCD) face unique challenges in engaging with cognitive-behavioural therapy (CBT), particularly the distress associated with exposure and response prevention (ERP) tasks. As digital delivery of CBT becomes increasingly widespread, questions remain about how the therapeutic alliance - a key predictor of treatment outcomes - is developed and sustained in this format. This study explored how adolescents and therapists experience the process of building and maintaining the therapeutic alliance during digital CBT for OCD, with particular attention to barriers, facilitators, and adaptations. Semi-structured interviews were conducted with six therapists and four adolescents who had participated in digital CBT for OCD. Although recruitment targeted ‘adolescents’, the client participants predominantly represented the upper end of adolescence, with all aged 18 or over (i.e. aligning with many definitions of emerging adulthood). For continuity with the study framing and service context, the term ‘adolescent’ is retained to denote older adolescents/emerging adults and interpret the findings with this developmental positioning in mind. A reflexive thematic analysis was used to identify patterns in participants’ experiences, highlighting both shared and divergent perspectives across the two groups. The analysis identified seven themes, illustrating both the opportunities and obstacles when fostering the alliance in digital settings. Therapists described making deliberate adaptations to humanise the digital space and maintain emotional presence, while adolescents emphasised the importance of privacy and developmentally-attuned approaches to support engagement. Technical and home-based disruptions, and the emotional distance of digital therapy were reported as barriers to openness - particularly during ERP tasks that rely on trust and in-the-moment support. Collaboration and flexibility emerged as essential strategies for overcoming these challenges, with both groups emphasising the importance of tailoring therapy to adolescents’ individual needs and daily environments. The findings underscore the importance of therapist adaptability, collaborative planning, and intentional rapport-building in digital CBT for OCD. Collectively, the themes point to concrete strategies - such as normalising the digital format, co-designing ERP tasks, and protecting privacy - that therapists can integrate into sessions to foster adolescent engagement and relational depth. Embedding these competencies into therapist training and service protocols may enhance digital CBT delivery and thus warrants systematic evaluation in future research

Plant Species Classification Using Evolving Ensemble and Siamese Networks

Image-based dried plant specimen identification poses a significant challenge due to the large number of possible classes and the extreme scarcity of labelled training samples. To tackle these limitations and mitigate classification biases, this research proposes a Particle Swarm Optimisation (PSO)-based weighted evolving ensemble model as well as a Siamese network for plant species classification. Specifically, we first diversify the base classifier pool by employing three networks, i.e. ResNet50, Xception, and VGG19, fine-tuned using the specimen samples. Besides the adoption of a mean average ensemble model, a weighted ensemble scheme with PSO-based optimal weighting factor generation is also utilised to integrate the outputs of the three base networks for tackling classification variances. In addition, to further tackle species classification with extremely imbalanced data, a Siamese network with ResNet50 as the backbone is utilised. Evaluated using a challenging FGVC6 data set with Melastomataceae images, the PSO-based weighted ensemble model is able to assign more influence to the best performing base networks for ensemble prediction and outperforms the traditional mean average ensemble method. Moreover, the Siamese network also obtains competitive performance for solving imbalanced specimen classification by performing comparing similarity scores between image embeddings

The phonological store of working memory:A critique and an alternative, perceptual-motor, approach to verbal short-term memory

A key quality of a good theory is its fruitfulness, one measure of which might be the degree to which it compels researchers to test it, refine it, or offer alternative explanations of the same empirical data. Perhaps the most fruitful element of Baddeley and Hitch’s (1974) Working Memory framework has been the concept of a short-term phonological store, a discrete cognitive module dedicated to the passive storage of verbal material that is architecturally fractionated from perceptual, language, and articulatory systems. This review discusses how the phonological store construct has served as the main theoretical springboard for an alternative perceptual-motor approach in which serial recall performance reflects the opportunistic co-opting of the articulatory planning system and, when auditory material is involved, the products of obligatory auditory perceptual organisation. It is argued that this approach, which rejects the need to posit a distinct short-term store, provides a better account of the two putative empirical hallmarks of the phonological store—the phonological similarity effect and the irrelevant speech effect—and that it shows promise too in being able to account for nonword repetition and word-form learning, the supposed evolved function of the phonological store. The neuropsychological literature cited as strong additional support for the phonological store concept is also scrutinised through the lens of the perceptual-motor approach for the first time and a tentative articulatory-planning deficit hypothesis for the ‘short-term memory’ patient profile is advanced. Finally, the relation of the perceptual-motor approach to other ‘emergent-property’ accounts of short-term memory is briefly considered