We present a simulation study based on a cognitive architecture that unifies various early language acquisition phenomena in laboratory and naturalistic settings. The model adaptively learns procedures through trial-and-error using general-purpose operators, guided by learned contextual associations to optimise future performance. For laboratory-based studies, simulated preferential focusing explains the delayed behavioural onset of statistical learning and the possible age-related decrease in algebraic processing. These findings suggest a link to continuous, implicit learning rather than explicit strategy acquisition. Moreover, procedures are not static but can evolve over time, and multiple plausible procedures may emerge for a given task. Besides, the same model provides a proof-of-concept for word-level phonological learning from naturalistic infant-directed speech, demonstrating how age-related processing efficiency may influence learning trajectories implicated in typical and atypical early language development. Furthermore, the artile discusses the broader implications for modelling other aspects of real-world language acquisition.

Various theories have been proposed in the field of second language (L2) sentence processing research and have significantly advanced our understanding of the mechanisms underlying L2 sentence interpretation processes. However, many existing theories have only been formulated verbally, and little progress has been made towards formal modelling. Formal modelling offers several advantages, including enhancing the clarity and verifiability of theoretical claims. This paper aims to address this gap in the literature by introducing formal computational modelling and demonstrating its application in L2 sentence processing research. Through practical demonstrations, the paper also emphasises the importance of formal modelling in the formulation and development of theory.

Knowledge and behaviour are transmitted from one individual to another through social learning and eventually disseminated across the population. People often learn useful behaviours socially through selective bias rather than random selection of targets. Prestige bias, or the tendency to selectively imitate prestigious individuals, has been considered an important factor in influencing human behaviour. Although its importance in human society and culture has been recognised, the formulation of prestige bias is less developed than that of other social learning biases. To examine the effects of prestige bias on cultural evolution theoretically, it is imperative to formulate prestige and investigate its basic properties. We reviewed two definitions: one based on first-order cues, such as the demonstrator's appearance and job title, and the other based on second-order cues, such as people's behaviour towards the demonstrator (e.g. people increasingly pay attention to prestigious individuals). This study builds a computational model of prestige bias based on these two definitions and compares the cultural evolutionary dynamics they generate. Our models demonstrate the importance of distinguishing between the two types of formalisation, because they can have different influences on cultural evolution.

In recent years, there has been an increasing interest in the research and development of hybrid airships for various applications. Airship design involves multiple design parameters from various disciplines that interact mutually. Existing design methodologies, however, are often limited to fixed shapes and geometry. This paper provides a comprehensive parametric design approach for the sizing of multi-lobed hybrid air vehicles for low- and high-altitude applications. The proposed design techniques are robust so that the designer has the freedom to change the number of lobes, the relative location of lobes, the envelope profile, and the optimiser for the design optimisation process. The outcomes of the proposed methodology are envelope volume, wetted surface area, length and span of the envelope, sizing and layout of the solar array, and sizing and layout of the fins. The modeling techniques highlighted in this paper are very efficient for the design and optimisation of multi-lobed airships in the conceptual design phase with a large design exploration space. The robustness of the shape generation algorithms is tested on some of the standard envelope profiles of airships. The effect of the shape and geometry of the multi-lobed envelope on added mass is demonstrated through the added mass estimation using Boundary Element Method.

Why do states engage in irredentism? Expanding on previous scholarship, this article advances a new theory with rationalist microfoundations that accounts for the incentives of both elites and citizens to support irredentism in democracies and dictatorships. Our model suggests irredentism is more likely when it enables political elites to provide a specific mix of private goods, public goods, and welfare transfers to citizens who desire them at the lowest tax rate. This leads to the prediction that irredentism is most likely in majoritarian democratic electoral systems and military dictatorships, and least likely in proportional electoral systems and single-party dictatorships. We test and find supportive evidence for these expectations using a comprehensive dataset covering all observed and potential irredentist cases from 1946 to 2014.

The ongoing coronavirus disease 2019 (COVID-19) pandemic is of global concern and has recently emerged in the US. In this paper, we construct a stochastic variant of the SEIR model to estimate a quasi-worst-case scenario prediction of the COVID-19 outbreak in the US West and East Coast population regions by considering the different phases of response implemented by the US as well as transmission dynamics of COVID-19 in countries that were most affected. The model is then fitted to current data and implemented using Runge-Kutta methods. Our computation results predict that the number of new cases would peak around mid-April 2020 and begin to abate by July provided that appropriate COVID-19 measures are promptly implemented and followed, and that the number of cases of COVID-19 might be significantly mitigated by having greater numbers of functional testing kits available for screening. The model is also sensitive to assigned parameter values and reflects the importance of healthcare preparedness during pandemics.

The computational BIA+ model (Dijkstra & Van Heuven, 2002) has provided a useful account for bilingual word recognition, while the verbal (pre-quantitative) RHM (Kroll & Stewart, 1994) has often served as a reference framework for bilingual word production and translation. According to Brysbaert and Duyck (2010), a strong need is felt for a unified implemented account of bilingual word comprehension, lexical-semantic processing, and word production. With this goal in mind, we built a localist-connectionist model, called Multilink, which integrates basic assumptions of both BIA+ and RHM. It simulates the recognition and production of cognates (form-similar translation equivalents) and non-cognates of different lengths and frequencies in tasks like monolingual and bilingual lexical decision, word naming, and word translation production. It also considers effects of lexical similarity, cognate status, relative L2-proficiency, and translation direction. Model-to-model comparisons show that Multilink provides higher correlations with empirical data than both IA and BIA+ models.

Stylistic composition is a creative musical activity, in which students as well as renowned composers write according to the style of another composer or period. We describe and evaluate two computational models of stylistic composition, called Racchman-Oct2010 (random constrained chain of Markovian nodes, October 2010) and Racchmaninof-Oct2010 (Racchman with inheritance of form). The former is a constrained Markov model, and the latter embeds this model in an analogy-based design system. Racchmaninof-Oct2010 applies a pattern discovery algorithm called SIACT and a perceptually validated formula for rating pattern importance, to guide the generation of a new target design from an existing source design. A listening study is reported concerning human judgments of music excerpts that are, to varying degrees, in the style of mazurkas by Frédéric Chopin (1810–1849). The listening study acts as an evaluation of the two computational models and a third, benchmark system, called Experiments in Musical Intelligence. Judges' responses indicate that some aspects of musical style, such as phrasing and rhythm, are being modeled effectively by our algorithms. Judgments are also used to identify areas for future improvements. We discuss the broader implications of this work for the fields of engineering and design, where there is potential to make use of our models of hierarchical repetitive structure.