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Item type: Item , Access status: Open Access , Foundations of Whatifiness: Asking Counterfactual What if? Questions through Quantum Principles for Adaptive Decision-making(Carleton University, 2026) Singer, Justin MatthiasThe experiment presented here serves as the proof of concept for a reinforcement learning algorithm that is capable of adapting to environmental conditions outside the scope of the scenario in which it is trained. In order to evaluate this property, we train all of our control and experimental models on a preset environmental configuration based on the Minigrid package. This training process is followed by a testing stage, in which each model is deployed on a collection of Minigrid environment configurations that differ from that of the training scenario. The adaptability of the models evaluated in our experiment is measured according to the reward scores received over several episodes on each test grid. In this investigation, we introduce a novel classical-quantum hybrid reinforcement learning method that exploits decoherence effects in simulated quantum states as a principle of counterfactual sampling. Our technique employs an on-policy actor-critic model in which the quantum layer of the actor network is based on a tree tensor network circuit, while the critic network is constructed according to a classical-quantum hybrid transformer model with quantum self-attention layers. Counterfactual samples are generated through random bit flip operations in the quantum layers of the critic network. Each sampling produces a corresponding value function estimate from the critic network, after which these estimates, along with the value function estimate corresponding to the base inputs, are used to calculate a refined value function estimate for the optimization of the actor network. Our transformer critic architecture diverges from more traditional critic network structures by using the most recent policy representation array from the actor network in addition to the observation data received from the environment.Item type: Item , Access status: Open Access , Mainstreaming on the Mediterranean: The Rassemblement National in Perpignan(Carleton University, 2026) Nohr, LiamWhen Louis Aliot of the Rassemblement National was elected mayor of Perpignan in 2020, a familiar question arose: would the far right moderate once in office? This thesis argues the question is the wrong one. Drawing on sentence-level content analysis of 940 coded segments from the mayor's municipal magazine and the regional newspaper L'Indépendant across 2021–2024, it shows that what changed in Perpignan was not what the RN claimed but how it claimed it. Mayoral discourse shifted from performance-based justification toward procedural conformity, while media coverage increasingly processed RN governance through technocratic rather than ideological frames. Far-right positions were not abandoned, they were repackaged in the language of administration. The thesis calls this process procedural sedimentation: a distinct mechanism of far-right mainstreaming in which authority consolidates not through ideological convergence but through the quiet absorption of conflict into institutional grammar. Normalization did not announce itself. It accumulated.Item type: Item , Access status: Open Access , A Representational Language for 3D Spatial Memories(Carleton University, 2026) Henry, Rebecca JaneAlthough spatial memories have been researched for decades, there are only a few frameworks capable of describing them. These frameworks are limited, however, as they primarily describe spatial relationships (e.g., the locations of objects) and consistently omit information that the mind would preserve. To combat this, a psychologically realistic spatial language (PRSL) is proposed. The PRSL aims to comprehensively represent 3D spatial memories, resembling human spatial memories as closely as possible. The PRSL will provide a standardized method of comprehensively describing 3D spaces, which has applications in cognitive modelling, robotics, and AI. To explore applications of the PRSL, and evaluate it, an LLM was prompted with the PRSL to generate a database of 3D spatial episodic artificial memories (SEAM-DB). SEAM-DB will also be the first database of artificial spatial memories, and it could even contribute to the exploration of LLMs’ spatial skills.Item type: Item , Access status: Open Access , Translational Regulation in Excitatory Neurons Controls Stress Reactivity and the Antidepressant Response to Ketamine(Carleton University, 2026) Baranyi Nicholls, SebastianMajor depressive disorder (MDD) is a leading cause of disability worldwide, with nearly one-third remaining treatment-resistant. Chronic stress is a major risk factor for MDD, whereas acute stress is adaptive and mediated by hypothalamic-pituitary-adrenal axis activation. Ketamine produces rapid antidepressant effects, partly through mammalian target of rapamycin complex 1 (mTORC1) signalling, which phosphorylates 4E-Binding Protein 1 and 2 (4E-BPs) to promote synaptic plasticity. This thesis examines the role of 4E-BP signalling in excitatory forebrain (Camk2a-positive) neurons in behavioural and endocrine responses to acute (ARS) and chronic (CVS) stress, and in ketamine's antidepressant effect. We found that ARS increased grooming and corticosterone in both sexes, with attenuated grooming in male DKO mice only. In CVS, DKO mice showed resilience to stress-induced behavioural deficits, while ketamine reversed these deficits in control mice. This work deepens our understanding of cellular factors controlling stress response and how ketamine produces therapeutic effects.Item type: Item , Access status: Open Access , Beyond the Literal: How Autism Shapes Pragmatic Language Understanding(Carleton University, 2026) Maleki, FatemehThis thesis examines whether pragmatic language differences in autistic adults reflect a global impairment or vary across domains of pragmatic processing. A total of 443 adults (59 autistic, 384 neurotypical) completed a battery of tasks assessing three components of pragmatic comprehension: conversational maxims, causal inferences, and prosody. The results revealed a significant Group × Task interaction, indicating that group differences were not uniform across domains. Autistic participants showed the largest differences from the control neurotypical group in maxim comprehension, smaller differences in prosodic interpretation, and minimal differences in understanding of causal inferences. Exploratory clustering analyses further identified heterogeneous performance profiles not aligned with diagnostic group. Individual differences in social cognition, nonverbal reasoning, and language proficiency were associated with pragmatic performance, whereas autistic trait severity was not. These findings suggest that pragmatic language in autism is better characterized as a multidimensional construct with domain-specific variability, rather than a single, global deficit.
