Cyberchondria, Coronavirus, and Cybercrime

Humans are adapting to and increasingly relying on technology particularly in times of global crisis. As online audiences increase, so does the risk of cybercrime. The impact of the COVID-19 pandemic is discussed in the context of health anxiety, the infodemic and cyberchondria, along with cybercriminal exploitation of pandemic-induced human anxiety and psychological vulnerability. Health anxiety, uncertainty, social isolation, changes to work-life practices, information seeking, mistrust of public health organisations, and the spread of false information all arguably intersect – leading to a global state of human vulnerability and therefore presenting opportunities for cybercriminals. There is a requirement for global agencies such as the United Nations, the WHO, INTERPOL, and governments to take action. Police agencies worldwide need to extrapolate learnings regarding the current pandemic and attendant increase in cybercrime and based on those findings move to form a global coalition with industry partners to investigate, predict, and prevent a potential future cybercrime pandemic.

The Important Role of Global State for Multi-Agent Reinforcement Learning

Environmental information plays an important role in deep reinforcement learning (DRL). However, many algorithms do not pay much attention to environmental information. In multi-agent reinforcement learning decision-making, because agents need to make decisions combined with the information of other agents in the environment, this makes the environmental information more important. To prove the importance of environmental information, we added environmental information to the algorithm. We evaluated many algorithms on a challenging set of StarCraft II micromanagement tasks. Compared with the original algorithm, the standard deviation (except for the VDN algorithm) was smaller than that of the original algorithm, which shows that our algorithm has better stability. The average score of our algorithm was higher than that of the original algorithm (except for VDN and COMA), which shows that our work significantly outperforms existing multi-agent RL methods.

Distributed estimation and control of a four-tank process

A multivariable process of four interconnected water tanks is considered for modeling and control. The objective of the current study is to design and implement a distributed control and estimation (DEC) for a multivariable four-tank process. Distributed model and inter-nodal communication structure are derived from global state–space matrices, thus combining the topology of plant flow sheet and the interaction dynamics across the plant subunits. Using experimental data, the process dynamics and disturbance effects are modeled. A typical lab-scale system was simulated and the obtained results demonstrated the potential of the DEC algorithm.

The Global State of Democracy Indices Technical Procedures Guides, Version 5 (2021)

The Global State of Democracy is a biennial report that aims to provide policymakers with an evidence-based analysis of the state of global democracy, supported by the Global State of Democracy (GSoD) Indices, in order to inform policy interventions and identify problem-solving approaches to trends affecting the quality of democracy around the world. The third edition of the report provides analyses of the current trends in democracy and human rights at the national, regional, and global levels, with special attention to the effects of the Covid-19 pandemic. This document presents revised and updated information about all the variables included in the GSoD indices data set that enabled the construction of Version 5 of the GSoD Indices, which depicts democratic trends at the country, regional and global levels across a broad range of different attributes of democracy in the period 1975–2020. The data underlying the GSoD Indices is based on a total of 116 indicators developed by various scholars and organizations using different types of source, including expert surveys, standards-based coding by research groups and analysts, observational data and composite measures.

The Global State of Democracy Indices Methodology, Conceptualization and Measurement Framework, Version 5 (2021)

The Global State of Democracy is a biennial report that aims to provide policymakers with an evidence-based analysis of the state of global democracy, supported by the Global State of Democracy (GSoD) Indices, in order to inform policy interventions and identify problem-solving approaches to trends affecting the quality of democracy around the world. This document revises and updates the conceptual and measurement framework that guided the construction of Version 5 of the GSoD Indices, which depicts democratic trends at the country, regional and global levels across a broad range of different attributes of democracy in the period 1975–2020. The data underlying the GSoD Indices is based on a total of 116 indicators developed by various scholars and organizations using different types of source, including expert surveys, standards-based coding by research groups and analysts, observational data and composite measures.

The Global State of Democracy Indices Codebook, Version 5 (2021)

The Global State of Democracy is a biennial report that aims to provide policymakers with an evidence-based analysis of the state of global democracy, supported by the Global State of Democracy Indices (GSoD Indices), in order to inform policy interventions and identify problem-solving approaches to trends affecting the quality of democracy around the world. This document presents revised and updated information about all the variables included in the GSoD indices data set that enabled the construction of Version 5 of the GSoD Indices, which depicts democratic trends at the country, regional and global levels across a broad range of different attributes of democracy in the period 1975–2020. The data underlying the GSoD Indices is based on a total of 116 indicators developed by various scholars and organizations using different types of source, including expert surveys, standards-based coding by research groups and analysts, observational data and composite measures.

Decentralized Multiagent Actor-Critic Algorithm Based on Message Diffusion

The exponential explosion of joint actions and massive data collection are two main challenges in multiagent reinforcement learning algorithms with centralized training. To overcome these problems, in this paper, we propose a model-free and fully decentralized actor-critic multiagent reinforcement learning algorithm based on message diffusion. To this end, the agents are assumed to be placed in a time-varying communication network. Each agent makes limited observations regarding the global state and joint actions; therefore, it needs to obtain and share information with others over the network. In the proposed algorithm, agents hold local estimations of the global state and joint actions and update them with local observations and the messages received from neighbors. Under the hypothesis of the global value decomposition, the gradient of the global objective function to an individual agent is derived. The convergence of the proposed algorithm with linear function approximation is guaranteed according to the stochastic approximation theory. In the experiments, the proposed algorithm was applied to a passive location task multiagent environment and achieved superior performance compared to state-of-the-art algorithms.

Program Verification with Separation Logic and Rely Guarantee

<p>This thesis explores two kinds of program logics that have become important for modern program verification - separation logic, for reasoning about programs that use pointers to build mutable data structures, and rely guarantee reasoning, for reasoning about shared variable concurrent programs. We look more closely into the motivations for merging these two kinds of logics into a single formalism that exploits the benefits of both approaches - local, modular, and explicit reasoning about interference between threads in a shared memory concurrent program. We discuss in detail two such formalisms - RGSep and Local Rely Guarantee (LRG), in particular we analyse how each formalism models program state and treats the distinction between global state (shared by all threads) and local state (private to a given thread) and how each logic models actions performed by threads on shared state, and look into the proof rules specifically for reasoning about atomic blocks of code. We present full examples of proofs in each logic and discuss their differences. This thesis also illustrates how a weakest precondition semantics for separation logic can be used to carry out calculational proofs. We also note how in essence these proofs are data abstraction proofs showing that a data structure implements some abstract data type, and relate this idea to a classic data abstraction technique by Hoare. Finally, as part of the thesis we also present a survey of tools that are currently available for doing manual or semi-automated proofs as well as program analyses with separation logic and rely guarantee.</p>

Program Verification with Separation Logic and Rely Guarantee

<p>This thesis explores two kinds of program logics that have become important for modern program verification - separation logic, for reasoning about programs that use pointers to build mutable data structures, and rely guarantee reasoning, for reasoning about shared variable concurrent programs. We look more closely into the motivations for merging these two kinds of logics into a single formalism that exploits the benefits of both approaches - local, modular, and explicit reasoning about interference between threads in a shared memory concurrent program. We discuss in detail two such formalisms - RGSep and Local Rely Guarantee (LRG), in particular we analyse how each formalism models program state and treats the distinction between global state (shared by all threads) and local state (private to a given thread) and how each logic models actions performed by threads on shared state, and look into the proof rules specifically for reasoning about atomic blocks of code. We present full examples of proofs in each logic and discuss their differences. This thesis also illustrates how a weakest precondition semantics for separation logic can be used to carry out calculational proofs. We also note how in essence these proofs are data abstraction proofs showing that a data structure implements some abstract data type, and relate this idea to a classic data abstraction technique by Hoare. Finally, as part of the thesis we also present a survey of tools that are currently available for doing manual or semi-automated proofs as well as program analyses with separation logic and rely guarantee.</p>

Democratic Institutions and Practices and the Impact on Covid-19 Outcomes: Global State of Democracy 2021 Thematic Paper

Despite the narratives of authoritarian states, the concerns of journalists and public intellectuals in democracies, and the results of some early studies, this paper shows that democracies fare no worse than authoritarian regimes in combating the Covid-19 pandemic. Democracy is not associated with higher Covid-19 death rates, nor is it associated with lower vaccination rates. Moreover, among many democratic countries, high levels of key democratic components -such as fundamental rights and impartial administration—seem to help prevent deaths and boost vaccination rates. These conclusions are based on statistical analyses of democracy components, as measured by International IDEA’s Global State of Democracy (GSoD) Indices, and the reported Covid-19 death rates and Covid-19 vaccination rates in all countries of the world with a population of at least one million people.