Utilising Assured Multi-Agent Reinforcement Learning within safety-critical scenarios

Multi-agent reinforcement learning allows a team of agents to learn how to work together to solve complex decision-making problems in a shared environment. However, this learning process utilises stochastic mechanisms, meaning that its use in safety-critical domains can be problematic. To overcome this issue, we propose an Assured Multi-Agent Reinforcement Learning (AMARL) approach that uses a model checking technique called quantitative verification to provide formal guarantees of agent compliance with safety, performance, and other non-functional requirements during and after the reinforcement learning process. We demonstrate the applicability of our AMARL approach in three different patrolling navigation domains in which multi-agent systems must learn to visit key areas by using different types of reinforcement learning algorithms (temporal difference learning, game theory, and direct policy search). Furthermore, we compare the effectiveness of these algorithms when used in combination with and without our approach. Our extensive experiments with both homogeneous and heterogeneous multi-agent systems of different sizes show that the use of AMARL leads to safety requirements being consistently satisfied and to better overall results than standard reinforcement learning

T-cell recognition of chemicals, protein allergens and drugs: towards the development of in vitro assays

Chemicals can elicit T-cell-mediated diseases such as allergic contact dermatitis and adverse drug reactions. Therefore, testing of chemicals, drugs and protein allergens for hazard identification and risk assessment is essential in regulatory toxicology. The seventh amendment of the EU Cosmetics Directive now prohibits the testing of cosmetic ingredients in mice, guinea pigs and other animal species to assess their sensitizing potential. In addition, the EU Chemicals Directive REACh requires the retesting of more than 30,000 chemicals for different toxicological endpoints, including sensitization, requiring vast numbers of animals. Therefore, alternative methods are urgently needed to eventually replace animal testing. Here, we summarize the outcome of an expert meeting in Rome on 7 November 2009 on the development of T-cell-based in vitro assays as tools in immunotoxicology to identify hazardous chemicals and drugs. In addition, we provide an overview of the development of the field over the last two decades

Towards a Conceptual Design and Semantic Modeling Approach for Innovative Modular Products

Part 5: TRIZ and Knowledge ManagementInternational audienceTo meet a demand more and more personalized for different users, the products must be innovative but also reliable, modular with good maintainability. Considering all these requirements in the design and modeling process would facilitate an evaluation of the behavioral performance of the future product. Most works deal with aspects related to functional criteria whereas behavior is rarely taken into account in the search for solutions. In this paper, we propose a design approach for innovative modular products, easily maintainable and adaptable to different user profiles. In order to evaluate the modularity, we propose a method of semantic modeling. The semantic model obtained makes it possible to identify innovative modular solution concepts by solving technical contradictions taking into account both the functional characteristics and the behavioral performances. As an illustration, a case study is outlined

How to involve inhabitants in urban design planning by using digital tools?: An overview on a state of the art, key challenges and promising approaches

Different cases of public disagreement in different European countries have shown recently that perusing a thorough planning process is by no means a guarantee for a broad public acceptance of an envisioned urban project. Consequently, the employment of digital media and tools to enable participation of inhabitants in urban planning processes on a massive scale is a promising, but currently not comprehensively analyzed approach. Our research activities are intended to gain an overview on a state of the art of research on communication channels, methods and best practices as well as to identify key challenges and promising strategies and tools to overcome these challenges with specific regards to large numbers of users and digital supported approaches. The latter aspects comprise the investigation of phenomena like participant selection, framing effects and gamified approaches for digital-mediated participatory processes as well as native language processing techniques to examine opinions as well as ideas of relevance from massive public feedback. To examine, we performed literature reviews of several hundred research articles, investigated cases in Germany, France and the Netherlands by interviews and workshops with stakeholders and employed methods of prototyping to conceptualize, develop and assess some promising approaches such as sentiment analysis in detail.</p

A Method to Formulate Problem in Initial Analysis of Inventive Design

Part 6: Tools to Support Early Design PhasesInternational audienceInitial Analysis is one of the most important phases of Inventive Design, where designers apply the existing methods to formulate a problem. One of these methods is problem graph, which is a powerful tool to translate the knowledge, collected from available documents and data, into a graphical model. However, this graph, by considering today’s competitive world, does not have the agility to present the essential information for applying in the next phase of Inventive Design. The aim of this article is to introduce a new method, which makes a designer able to formulate an appropriate problem, according to the objectives, without wasting time. This method, along with TRIZ, could create an agile design process. An example is done to illustrate better the process

A Smart System for Haptic Quality Control: A Knowledge-Based Approach to Formalize the Sense of Touch In

International audienc