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Over the past decade, the continuous surge in cloud computing demand has intensified data center workloads, leading to significant carbon emissions and driving the need for improving their efficiency and sustainability. This paper focuses on the optimal allocation problem of batch compute loads with temporal and spatial flexibility across a global network of data centers. We propose a bilevel game-theoretic solution approach that captures the inherent hierarchical relationship between supervisory control objectives, such as carbon reduction and peak shaving, and operational objectives, such as priority-aware scheduling. Numerical simulations with real carbon intensity data demonstrate that the proposed approach successfully reduces carbon emissions while simultaneously ensuring operational reliability and priority-aware scheduling.

Game-theoretic MPC (or Receding Horizon Games) is an emerging control methodology for multi-agent systems that generates control actions by solving a dynamic game with coupling constraints in a receding-horizon fashion. This control paradigm has recently received an increasing attention in various application fields, including robotics, autonomous driving, traffic networks, and energy grids, due to its ability to model the competitive nature of self-interested agents with shared resources while incorporating future predictions, dynamic models, and constraints into the decision-making process. In this work, we present the first formal stability analysis based on dissipativity and monotone operator theory that is valid also for non-potential games. Specifically, we derive LMI-based certificates that ensure asymptotic stability and are numerically verifiable. Moreover, we show that, if the agents have decoupled dynamics, the numerical verification can be performed in a scalable manner. Finally, we present tuning guidelines for the agents' cost function weights to fulfill the certificates and, thus, ensure stability.

The vast majority of products we use daily are supplied to us through complex global supply chains that transform raw materials into finished goods and distribute them to end consumers. This paper proposes a modeling methodology for dynamic competitive supply chains based on game theory and model predictive control. We model each manufacturer in the supply chain as a rational utility maximizing agent that selects their actions by finding an open-loop generalized Nash equilibrium of a multi-stage game. To react to competitors and the state of the market, every agent re-plans their actions in a receding horizon manner based on estimates of market and supplier parameters thereby creating an approximate closed-loop equilibrium policy. We demonstrate through numerical simulations that this modeling approach is computationally tractable and generates economically interpretable behaviors in a variety of settings such as demand spikes, supply shocks, and information asymmetry.

Medical drug infusion problems pose a combination of challenges such as nonlinearities from physiological models, model uncertainty due to inter- and intra-patient variability, as well as strict safety specifications. With these challenges in mind, we propose a novel real-time Nonlinear Model Predictive Control (NMPC) scheme based on projected gradient descent iterations. At each iteration, a small number of steps along the gradient of the NMPC cost is taken, generating a suboptimal input which asymptotically converges to the optimal input. We retrieve classical Lyapunov stability guarantees by performing a sufficient number of gradient iterations until fulfilling a stopping criteria. Such a real-time control approach allows for higher sampling rates and faster feedback from the system which is advantageous for the class of highly variable and uncertain drug infusion problems. To demonstrate the controller's potential, we apply it to hypnosis control in anesthesia of two interacting drugs. The controller successfully regulates hypnosis even under disturbances and uncertainty and fulfils benchmark performance criteria.

Distributed energy storage and flexible loads are essential tools for ensuring stable and robust operation of the power grid in spite of the challenges arising from the integration of volatile renewable energy generation and increasing peak loads due to widespread electrification. This paper proposes a demand-side management policy to coordinate self-interested energy prosumers based on receding horizon games, i.e., a closed-loop receding-horizon implementation of game-theoretic day-ahead planning. Practical stability and recursive constraint satisfaction of the proposed feedback control policy is proven under symmetric pricing assumptions using tools from game theory and economic model predictive control. Our numerical studies show that the proposed approach is superior to standard open-loop day-head implementations in terms of peak-shaving, disturbance rejection, and control performance.

For more than 25 years, the Adult Participation in Learning Survey has provided a unique insight into adult learning across the UK. It adopts a deliberately broad definition of learning, reflecting the fact that learning is about so much more than formal courses and qualifications. The good news is that, after a decade of declines during the 2010s, participation in learning remains back at levels last seen in the early 2000s: around two in five adults (42 percent) say they have taken part in learning at some point in the last three years. The survey also demonstrates a shift in the number of adults learning independently and informally, with interest sparked during the pandemic and the rise of lockdown learning and helping to fill the gap as formal and publicly-funded learning fell over the previous decade. In the same way, the step change during the pandemic in learning at least partly online has sustained: 68 percent of adults said at least part of their learning took place online. However, that doesn't mean we don't need to see increases in formal learning -- qualifications can give people currency in the labour market where this is their reason for learning, and our research has shown employer investment in training has fallen 28 percent since 2005, holding back productivity. This is the latest survey in a series of over 26 years. [For "Adult Participation in Learning Survey 2021" see ED627560]

One of the most important reforms to the apprenticeship system in recent years has been the transition from apprenticeship frameworks to employer-designed standards. However, the completion rates for these standards are much lower than for frameworks, with large numbers of apprentices withdrawing early from their programmes. It is vital to understand why so many apprentices do not complete their programmes, and how they could be supported to do so, in order to deliver better results for employers, individuals and the taxpayer. On behalf of the St Martin's Group, we have conducted research to explore the experiences, outcomes and destinations of apprentices who complete their programme and those who do not. The research has involved a large-scale survey of apprentices, including a uniquely large sample of non-completers, with follow-up qualitative interviews. It explores: (1) Destinations and outcomes for apprentices who complete their programme and those who do not; (2) ?Reasons for non-completion of apprenticeships?, and factors that lead to completion or non-completion?; and (3) Support that could help apprentices to complete their programme. [This report was produced with The St Martin's Group.]

Participation in adult essential skills learning has fallen significantly over the past decade across the UK. In our previous report with the Skills for Life Alliance "Getting the Basics Right: The Case for Action on Adult Basic Skills" (ED618568), we explored the social, economic and health benefits of having a solid foundation in essential skills. For the Alliance's latest report, Learning and Work Institute has investigated innovative, place-based interventions in three Mayoral Combined Authority areas where the number of people learning essential skills has declined the most (West of England, South Yorkshire and Liverpool City Region). Here, we have looked at what works at a local level to engage people in learning essential skills. This research highlights several policy areas where urgent action is needed: (1) Improving essential skills should be a national and local priority, with a sustained effort to engage adults and employers and ambition to increase participation and achievement to at least 2010 levels; (2) A flexible approach to English, maths and ESOL provision can help increase participation; and (3) It's vital to tailor messaging and course content around adult's needs and interests. Other recommendations look at reaching adults who lack confidence or who face other barriers around access and time; and forging better partnerships working with employers, providers and community organisations to embed learning.

It is 25 years since the first adult participation in learning survey, and this one is published during Learning and Work Institute's centenary year. This year's survey shows that 44% of adults have taken part in learning in the last three years. That's an increase on the record lows found in 2019 and marks the first rise in participation since 2015. However, the data also shows stark inequalities in who participates in learning: (1) Adults in lower socio-economic groups (DE) are twice as likely to not have participated in learning since leaving full-time education than those in higher socio-economic groups (AB); (2) Respondents who stayed in education until at least the age of 21 are twice as likely to be learning than those who left aged 16 or under (56% versus 28%); (3) The majority (55%) of full-time workers are taking part in learning, compared to 45% of unemployed adults seeking work. Learning and Work Institute has been undertaking the Adult Participation in Learning Survey on an almost annual basis for 25 years. The survey provides a unique overview of the level of participation in learning by adults, with a detailed breakdown of who participates and who does not. The survey deliberately adopts a broad definition of learning, including a wide range of formal, non-formal and informal learning, far beyond the limits of publicly offered educational opportunities for adults. Each year, a representative sample of approximately 5,000 adults aged 17 and over across the UK are provided with the following definition of learning and asked when they last took part, as well as how likely they are to take part in learning during the next three years. [For "Learning through Lockdown: Findings from the 2020 Adult Participation in Learning Survey" see ED611898.]