Inductive and Functional Types in Ludics

Ludics is a logical framework in which types/formulas are modelled by sets of terms with the same computational behaviour. This paper investigates the representation of inductive data types and functional types in ludics. We study their structure following a game semantics approach. Inductive types are interpreted as least fixed points, and we prove an internal completeness result giving an explicit construction for such fixed points. The interactive properties of the ludics interpretation of inductive and functional types are then studied. In particular, we identify which higher-order functions types fail to satisfy type safety, and we give a computational explanation

An Interpretation of CCS into Ludics

Abstract Starting from works aimed at extending the Curry-Howard correspondence to process calculi through linear logic, we give another Curry-Howard counterpart for Milner's Calculus of Communicating Systems (CCS) by taking Ludics as the target system. Indeed interaction, Ludics' dynamic, allows to fully represent both the non-determinism and non-confluence of the calculus. We give an interpretation of CCS processes into carefully defined behaviours of Ludics using a new construction, called directed behaviour, that allows controlled interaction paths by using pruned designs. We characterize the execution of processes as interaction on behaviours, by implicitly representing the causal order and conflict relation of event structures. As a direct consequence, we are also able to interpret deadlocked processes, and identify deadlock-free ones

Matheuristics for robust optimization: application to real-world problems

In the field of optimization, the perspective that the problem data are subject to uncertainty is gaining more and more interest. The uncertainty in an optimization problem represents the measurement errors during the phase of collecting data, or unforeseen changes in the environment while implementing the optimal solution in practice. When the uncertainty is ignored, an optimal solution according to the mathematical model can turn out to be far from optimal, or even infeasible in reality. Robust optimization is an umbrella term for mathematical modelling methodologies focused on finding solutions that are reliable against the data perturbations caused by the uncertainty. Among the relatively more recent robust optimization methodologies, an important concept studied is the degree of conservativeness, which can be explained as the amount of targeted reliability against the uncertainty while looking for a solution. Because the reliability and solution cost usually end up being conflicting objectives, it is important for the decision maker to be able to configure the conservativeness degree, so that the desired balance between the cost and reliability can be obtained, and the most practical solution can be found for the problem at hand. The robust optimization methodologies are typically proposed within the framework of mathematical programming (i.e. linear programming, integer programming). Thanks to the nature of mathematical programming, these methodologies can find the exact optimum, according to the various solution evaluation perspectives they have. However, dependence on mathematical programming might also mean that such methodologies will require too much memory from the computer, and also too much execution time, when large-scale optimization problems are considered. A common strategy to avoid the big memory and execution time requirements of mathematical programming is to use metaheuristic optimization algorithms for solving large problem instances.In this research, we propose an approach for solving medium-to-large-sized robust optimization problem instances. The methodology we propose is a matheuristic (i.e. a hybridization of mathematical programming and metaheuristic). In the matheuristic approach we propose, the mathematical programming part handles the uncertainty, and the metaheuristic part handles the exploration of the solution space. Since the exploration of the solution space is entrusted onto the metaheuristic search, we can obtain practical near-optimal solutions while avoiding the big memory and time requirements that might be brought by pure mathematical programming methods. The mathematical programming part is used for making the metaheuristic favor the solutions which have more protections against the uncertainty. Another important characteristic of the methodology we propose is concurrency with information exchange: we concurrently execute multiple processes of the matheuristic algorithm, each process taking the uncertainty into account with a different degree of conservativeness. During the execution, these processes exchange their best solutions. So, if a process is stuck on a bad solution, it can realize that there is a better solution available thanks to the information exchange, and it can get unstuck. In the end, the solutions of these processes are collected into a solution pool. This solution pool provides the decision maker with alternative solutions with different costs and conservativeness degrees. Having a solution pool available at the end, the decision maker can make the most practical choice according to the problem at hand. In this thesis, we first discuss our studies in the field of robust optimization: a heuristic approach for solving a minimum power multicasting problem in wireless actuator networks under actuator distance uncertainty, and a linear programming approach for solving an aggregate blending problem in the construction industry, where the amounts of components found in aggregates are subject to uncertainty. These studies demonstrate the usage of mathematical programming for handling the uncertainty. We then discuss our studies in the field of matheuristics: a matheuristic approach for solving a large-scale energy management problem, and then a matheuristic approach for solving large instances of minimum power multicasting problem. In these studies, the usage of metaheuristics for handling the large problem instances is emphasized. In our study of solving minimum power multicasting problem, we also incorporate the mechanism of information exchange between different solvers. Later, we discuss the main matheuristic approach that we propose in this thesis. We first apply our matheuristic approach on a well-known combinatorial optimization problem: capacitated vehicle routing problem, by using an ant colony optimization as the metaheuristic part. Finally, we discuss the generality of the methodology that we propose: we suggest that it can be used as a general framework on various combinatorial optimization problems, by choosing the most appropriate metaheuristic algorithm according to the nature of the problem

Network Function Virtualization Service Delivery In Future Internet

This dissertation investigates the Network Function Virtualization (NFV) service delivery problems in the future Internet. With the emerging Internet of everything, 5G communication and multi-access edge computing techniques, tremendous end-user devices are connected to the Internet. The massive quantity of end-user devices facilitates various services between the end-user devices and the cloud/edge servers. To improve the service quality and agility, NFV is applied. In NFV, the customer\u27s data from these services will go through multiple Service Functions (SFs) for processing or analysis. Unlike traditional point-to-point data transmission, a particular set of SFs and customized service requirements are needed to be applied to the customer\u27s traffic flow, which makes the traditional point-to-point data transmission methods not directly used. As the traditional point-to-point data transmission methods cannot be directly applied, there should be a body of novel mechanisms that effectively deliver the NFV services with customized~requirements. As a result, this dissertation proposes a series of mechanisms for delivering NFV services with diverse requirements. First, we study how to deliver the traditional NFV service with a provable boundary in unique function networks. Secondly, considering both forward and backward traffic, we investigate how to effectively deliver the NFV service when the SFs required in forward and backward traffic is not the same. Thirdly, we investigate how to efficiently deliver the NFV service when the required SFs have specific executing order constraints. We also provide detailed analysis and discussion for proposed mechanisms and validate their performance via extensive simulations. The results demonstrate that the proposed mechanisms can efficiently and effectively deliver the NFV services under different requirements and networking conditions. At last, we also propose two future research topics for further investigation. The first topic focuses on parallelism-aware service function chaining and embedding. The second topic investigates the survivability of NFV services

Collections for people: museums' stored collections as a public resource

Collections in UK museums grew enormously in the latter half of the 20th century yet museum collections, mostly maintained at public expense, are perceived as an underused resource. The Museums Association’s 2005 report, Collections for the Future1, together with press comments and books such as Treasures on Earth (2002)2 and Fragments of the World (2005)3, brought this issue into sharp focus. Collections for People set out to understand the scale of museum stored collections, and the main parameters of their access and use: • What is the size and nature of collections as a resource? How are they distributed, geographically and among different types of museum? • How much are different types of collection used by people other than museum staff? What sort of people use collections? What do they use them for: research, teaching and learning, creative activities, visits for enjoyment such as store tours? • How do users perceive this service? Do museums actively market collections access? Do they publicise what is in their collections? • How do museums facilitate collections use? What are the factors associated with greater use of collections? What do museums see as the barriers to more use

Core Challenges in Embodied Vision-Language Planning

Recent advances in the areas of multimodal machine learning and artificial intelligence (AI) have led to the development of challenging tasks at the intersection of Computer Vision, Natural Language Processing, and Embodied AI. Whereas many approaches and previous survey pursuits have characterised one or two of these dimensions, there has not been a holistic analysis at the center of all three. Moreover, even when combinations of these topics are considered, more focus is placed on describing, e.g., current architectural methods, as opposed to also illustrating high-level challenges and opportunities for the field. In this survey paper, we discuss Embodied Vision-Language Planning (EVLP) tasks, a family of prominent embodied navigation and manipulation problems that jointly use computer vision and natural language. We propose a taxonomy to unify these tasks and provide an in-depth analysis and comparison of the new and current algorithmic approaches, metrics, simulated environments, as well as the datasets used for EVLP tasks. Finally, we present the core challenges that we believe new EVLP works should seek to address, and we advocate for task construction that enables model generalizability and furthers real-world deployment.Comment: 35 page

Routeing in military tourism: gamification as an implementation proposal

This dissertation approaches three main concepts, routeing applied to tourism, Military Tourism as a segment of Cultural Tourism and Gamification as a tool for tourist fruition, with the aim at establishing a link between them. Following a literature review from various authors in each of these areas, and after the establishment of a firm conceptual base, this project investigates the possible links between them. In this specific case the application of the benefits of gamification to promote the development of Military Tourism products and their organisation in military themed tourism routes. In conclusion this dissertation presents a guiding model explaining the use of different forms of game based technology to develop different Military Tourism products and how this tool can aid in the organisation in a Military Tourism Route

Language heritage and the UK public: successes and challenges of the UK heritage sector

The United Kingdom (UK) lacks a uniform approach to safeguarding intangible cultural heritage (ICH) such as language. The UK ratified the UNESCO Convention for the Safeguarding of Intangible Cultural Heritage in June 2024. In the absence of any UK-wide ICH framework, various approaches to safeguarding ICH have been taken at nation-level and at the level of (usually individual) museums, libraries and heritage groups. ICH can bring tangible heritage to life and give objects meaning and enhance the dynamic of cultural heritage. However, although language is included in the UNESCO Convention, to the extent that it is a “vehicle” of ICH, only recently have some museums and other organizations started to exhibit language. This article sets out our research findings from a pilot study undertaken in 2022 where we engaged with heritage sector professionals to identify how their organizations currently work with language heritage. Participants in our study voiced concerns that language heritage can be hard to encapsulate. We outline the challenges and successes of language heritage work, as well as the support that professionals felt they needed to undertake further work to enable them to engage with the public and local communities in order to safeguard this important aspect of ICH

Disablement in Prince George, BC: A qualitative, holistic and participatory exploration.

(dis)Abled people are frequently faced with barriers to their mobility when navigating the built environment, especially in colder climates yet little is known about this experience in northern BC. Using downtown Prince George as a study area, my research examines the lived experience of (dis)Ability in a northern, ageing, resource-based city and seeks to gain an understanding of what barriers are, how they impact (dis)Abled people, and why environments are disabling. Using go-along interviews, I found that barriers are often characteristics of the built and seasonal environment. Although generalizations cannot be made between individuals, the results suggest that barriers are connected to the presence of ableism in society and negatively impact (dis)Abled people participants described situations involving increased health issues, intense emotional stress and loss of autonomy. Exclusion, marginalization and discrimination are also uncovered as part of the lived experience of (dis)Ability in Prince George. I conclude that the first step towards an enabling environment is a social shift. --Leaf ii.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b184471