Agents that look at one another

International audienceDespite the fact that epistemic connectives are sometimes interpreted in concrete structures defined by means of runs and clock time functions, one of the things that strikes one when studying multiagent logics is how abstract their semantics are. Contrasting this fact is the fact that real agents like robots in everyday life and virtual characters in video games have strong links with their spatial environment. In this article, we introduce multiagent logics which semantics can be defined by means of purely geometrical notions: possible states are defined by means of the positions in ℝn occupied by agents and the sections of ℝn seen by agents whereas accessibility relations are defined by means of the ability of agents to imagine possible states compatible with what they currently see

Book Review: What Do We Talk About When We Talk About the Constitution?

It is certainly not surprising that America\u27s Unwritten Constitution is remarkably stimulating, informative, and challenging. You are surely correct that one cannot possibly understand the American constitutional system simply by reading the text of the Constitution (or, for that matter, reading decisions of the judiciary ostensibly interpreting the text). Instead, one must not only look at long-established American practices but also at social movements and transcendent moments in American history-the Gettysburg Address and Martin Luther King\u27s Dream speech are two that you emphasize-that have provided the rationales for how we understand those practices (and, on occasion, become willing to transform them). Your Constitution is necessarily a living Constitution, for the American people, as active agents of their own constitutional destinies, are constantly debating one another about what constitutes its deep meanings; they constantly create new movements, which in turn generate new political leaders committed to particular understandings

RAMPART: A model for a regulatory-ready academic-led phase III trial in the adjuvant renal cell carcinoma setting

The development of therapeutics in oncology is a highly active research area for the pharmaceutical and biotechnology industries, but also has a strong academic base. Many new agents have been developed in recent years, most with specific biological targets. This has mandated the need to look at different ways to streamline the evaluation of new agents. One solution has been the development of adaptive trial designs that allow the evaluation of multiple agents, concentrating on the most promising agents while screening out those which are unlikely to benefit patients. Another way forward has been the growth of partnerships between academia and industry with the shared goal of designing and conducting high quality clinical trials which answer important clinical questions as efficiently as possible. The RAMPART trial (NCT03288532) brings together both of these processes in an attempt to improve outcomes for patients with locally advanced renal cell carcinoma (RCC), where no globally acceptable adjuvant strategy after nephrectomy currently exist. RAMPART is led by the MRC CTU at University College London (UCL), in collaboration with other international academic groups and industry. We aim to facilitate the use of data from RAMPART, (dependent on outcomes), for a future regulatory submission that will extend the license of the agents being investigated. We share our experience in order to lay the foundations for an effective trial design and conduct framework and to guide others who may be considering similar collaborations

Agentenbasierende Finanzmarktmodelle

In this thesis we look at different models of financial markets whose dynamic is based on the herding behaviour of the agents trading on the market. Kirman introduced the first model of this kind in the year 1991. We also consider another model that is introduced by Alfarano et al. in the year 2007. The basic assumptions of these models are that there is a fixed number of agents N, who trade on the market. These agents can be divided into two groups. We call them optimists and pessimists. The dynamic of these models is based on the fact that the agents switch between the two groups. Important for the state of the system is not the membership of each agent in one of the groups but the relation between optimistic and pessimistic agents. Due to the fact that the number of agents is constant, it is sufficient to look at the number of optimistic agents. In the two models mentioned above, the number of optimistic agents is modelled as a birth and death process. At first, we look at the behaviour of these birth and death processes in the case that the number of agents N tends to infinity. After that, we extend the model with another agent, representing further influences for the behaviour of the optimists and pessimists whom we call “super agent” and look at different limiting cases for this new model.In dieser Arbeit betrachten wir verschiedene Finanzmarktmodelle, deren Dynamik auf dem Kommunikationsverhalten der am Markt handelnden Agenten basiert. Das erste Modell dieser Art hat der Ökonom Kirman im Jahr 1991 beschrieben. Ein weiteres Modell, das wir betrachten, stammt aus einem Artikel von Alfarano et al. Aus dem Jahr 2007. Die Modelle basieren im Wesentlichen auf den folgenden Annahmen: Es gibt eine feste Anzahl Agenten N, die am Markt handeln. Diese Agenten lassen sich in zwei Gruppen aufteilen. Diese Gruppen werden wir als Optimisten und Pessimisten bezeichnen. Die Dynamik des Modells entsteht daraus, dass die Agenten zwischen diesen beiden Gruppen hin und her wechseln. In den beiden oben genannten Modellen wird die Dynamik des Modells durch einen Geburts- und Todesprozess modelliert. Zunächst betrachten wir das Verhalten dieser Geburts- und Todesprozesse für den Fall betrachten, dass die Anzahl der Agenten N gegen unendlich strebt. Danach erweitern wir das Modell und betrachten verschiedene Grenzverhalten im erweiterten Modell

Logic meets Wigner's Friend (and their Friends)

We take a fresh look at Wigner's Friend thought-experiment and some of its more recent variants and extensions, such as the Frauchiger-Renner (FR) Paradox. We discuss various solutions proposed in the literature, focusing on a few questions: what is the correct epistemic interpretation of the multiplicity of state assignments in these scenarios; under which conditions can one include classical observers into the quantum state descriptions, in a way that is still compatible with traditional Quantum Mechanics?; under which conditions can one system be admitted as an additional 'observer' from the perspective of another background observer?; when can the standard axioms of multi-agent Epistemic Logic (that allow "knowledge transfer" between agents) be applied to quantum-physical observers? In the last part of the paper, we propose a new answer to these questions, sketch a particular formal implementation of this answer, and apply it to obtain a principled solution to Wigner Friend-type paradoxes.Comment: 27 page

RAMPART : a model for a regulatory-ready academic-led phase III trial in the adjuvant renal cell carcinoma setting

AstraZeneca LP have provided an educational grant for the trial and free of charge durvalumab and tremelimumab. A small grant is also provided by Kidney Cancer UK. MRC CTU at UCL provides funding for staff working on the trial.The development of therapeutics in oncology is a highly active research area for the pharmaceutical and biotechnology industries, but also has a strong academic base. Many new agents have been developed in recent years, most with specific biological targets. This has mandated the need to look at different ways to streamline the evaluation of new agents. One solution has been the development of adaptive trial designs that allow the evaluation of multiple agents, concentrating on the most promising agents while screening out those which are unlikely to benefit patients. Another way forward has been the growth of partnerships between academia and industry with the shared goal of designing and conducting high quality clinical trials which answer important clinical questions as efficiently as possible. The RAMPART trial (NCT03288532) brings together both of these processes in an attempt to improve outcomes for patients with locally advanced renal cell carcinoma (RCC), where no globally acceptable adjuvant strategy after nephrectomy currently exist. RAMPART is led by the MRC CTU at University College London (UCL), in collaboration with other international academic groups and industry. We aim to facilitate the use of data from RAMPART, (dependent on outcomes), for a future regulatory submission that will extend the license of the agents being investigated. We share our experience in order to lay the foundations for an effective trial design and conduct framework and to guide others who may be considering similar collaborations.Publisher PDFPeer reviewe

Quantum machine learning and quantum biomimetics: A perspective

Quantum machine learning has emerged as an exciting and promising paradigm inside quantum technologies. It may permit, on the one hand, to carry out more efficient machine learning calculations by means of quantum devices, while, on the other hand, to employ machine learning techniques to better control quantum systems. Inside quantum machine learning, quantum reinforcement learning aims at developing "intelligent" quantum agents that may interact with the outer world and adapt to it, with the strategy of achieving some final goal. Another paradigm inside quantum machine learning is that of quantum autoencoders, which may allow one for employing fewer resources in a quantum device via a training process. Moreover, the field of quantum biomimetics aims at establishing analogies between biological and quantum systems, to look for previously inadvertent connections that may enable useful applications. Two recent examples are the concepts of quantum artificial life, as well as of quantum memristors. In this Perspective, we give an overview of these topics, describing the related research carried out by the scientific community.Comment: Invited Perspective article for Machine Learning: Science and Technology, 17 pages, 6 figures, 110 reference

Merit Transference and the Paradox of Merit Inflation

Many ethical systems hold that agents earn merit and demerit through their good and bad deeds. Some of these ethical systems also accept merit transference, allowing merit to be transferred, in certain circumstances, from one agent to another. In this article, I argue that there is a previously unrecognized paradox for merit transference involving a phenomenon I call “merit inflation”. With a particular focus on Buddhist ethics, I then look at the options available for resolving this paradox. I conclude that merit inflation poses a serious challenge for any ethical system that broadly permits the transfer of merit

A Hybrid Agent-Based and Equation Based Epidemiological Model for the Spread of Infectious Diseases

Infectious disease models are essential in understanding how an outbreak might occur and how best to mitigate an outbreak. One of the most important factors in modelling a disease is choosing an appropriate model and determining the assump tions needed to create the model. The main research questions this thesis addresses are how do we create a model for the spread of infectious diseases that captures heterogeneous agents without using an inordinate amount of computing power and how can we use that model to plan for future infectious disease outbreaks. We start our work by analysing and comparing equation based and agent based models and determine that an agent-based model’s stochasticity and ability to capture emerging results (complex and hard to explain results from interactions of agents) means that the agent-based model has an advantage in modelling the in dividual actions and complexities that make one infectious disease outbreak differ from another. Focusing on agent-based models, we take the model in two direc tions adding complexity and scaling up the model. Although adding complexity allows us to produce robust results, it increases run time so modelling anything beyond a small population is not feasible. Thus we focus on scaling up the model (from a town to a county) and determining what trade-offs need to be made to keep the model computationally tractable. With our scaled up model we look at characteristics of a town that come from its place in a network of towns, looking at how the centrality of a town affects how an outbreak spreads from a town and enters a town. We determine when a town has a high in degree centrality the i centrality of the other towns are not as important with respect to whether the outbreak will spread to the other towns. The additional agents in the scaled up model lead to an extended run time. In order to reduce run time we make an assumption about the importance of heterogeneous mixing when there is a large number of agents infected and create a hybrid agent-based and equation based model that switches between an agent based disease component and an equation based disease component based on a threshold of the number of agents infected. The hybrid model is able to save time compared to a fully agent-based model without losing a significant level of fidelity. This allows for the model to be scaled up to larger geographies and populations. Scaling the model to larger populations is essential in studying and testing the efficacy of interventions that would not be applicable at a smaller scale. To show this we use the hybrid model to analyse the effects of school closure policies across a network of towns, showing that closing both the town where an outbreak starts in and the town in the region with the highest in degree centrality can help mitigate an outbreak