SCENELAB: Scene Labelling by a Society of Agents; A Distributed Constraint Propagation System

This paper describes SCENELAB, a computer system for labelling line drawings of scenes in simple polyhedral worlds. The key idea behind SCENELAB is to bring together the concept of contraint-based filtering algorithms and the paradigm of societies of cooperating agents. The problem of finding labellings for pictures drawn from blocks world scenes has been taken as a sample application. Clearly, this makes SCENELAB no vision system, but we claim that a system designed along these lines could be part of a real vision system. Following e.g. Alan Mackworth, we argue that constraint exploitation on resp. between various representational levels is a key technique of ‘seeing things'. Furthermore, constraints and constraint propagation neatly fit into the framework of societies of agents, realized by asynchronuously concurrent processing units and message passing mechanisms. SCENELAB, as it is actually running, can be used to specify and solve arbitrary Labelling problems that can be seen as instances of a particular class of simple constraint problems based on finite, pseudo-transitive binary constraints. However, it is felt that the overall approach generalizes to arbitrary constraint problems. Emphasis is given to a mathematical model of the problem and its solution, to be able to specify the reasoning techniques of SCENELAB, and to identify the class of problems it can handle. I tried to shed some Light onto the methodological background of SCENELAB, which seems necessary to judge the achievements and disachievements of the present work. After some introductory chapters on the key concepts involved in SCENELAB, (scene) labelling problems, constraint propagation, and societies of agents, an overview on both the structure and behavior of SCENELAB is given in part B of the paper. In part C, then, an algebraic model is introduced, which serves as a base for discussing several approaches to labelling problems, namely Waltz's original Landmark algorithm, a synchronized parallel solution suggested by Azriel Rosenfeld, and clearly, the present approach. A proof of the correctness of SCENELABs algorithms is included. This proof takes into account the specifities of systems of asynchronously communicating agents where no global state is observable

The Governance of Disease Outbreaks

This edited volume is directed at experts in international law, practitioners in international institutions, and other experts who would like to familiarize themselves with the legal framework of infectious disease governance. Using the West African Ebola crisis as a case study, this book is part of a larger collaborative project on international health governance. Project partners are the Forschungsstätte der Evangelischen Studiengemeinschaft e.V. - Institute for Interdisciplinary Research and the Max Planck Institute for Comparative Public Law and International Law (MPIL). The authors explain the context and substantive legal framework of the Ebola crisis, while also highlighting its human rights aspects, institutional law (such as the debate on the securitization of health), and the limits to a purely legal approach to the subject. The authors are experts in public international law, public health, political science, and anthropology. With contributions by: Elif Askin, Susan L. Erikson, André den Exter, Robert Frau, Wolfgang Hein, Bonnie Kaiser, Hunter Keys, Michael Marx, Edefe Ojomo, Ilja Richard Pavone, Mateja Steinbrück Platise, Christian R. Thauer, Leonie Vierck, Pedro A. Villarreal, A. Katarina Weilert. Der Sammelband richtet sich an ein Fachpublikum von Völkerrechtlern, Praktikern in internationalen Institutionen und anderen Experten, die sich mit den rechtlichen Rahmenbedingungen der internationalen Governance ansteckender Krankheiten vertraut machen möchten. Fallbeispiel ist die Ebola-Krise in Westafrika. Der Band geht aus einem breiter angelegten Heidelberger Kooperationsprojekt zur „International Health Governance“ der Forschungsstätte der Evangelischen Studiengemeinschaft e.V. - Institut für interdisziplinäre Forschung (FEST) und des Max-Planck-Instituts für ausländisches öffentliches Recht und Völkerrecht (MPIL) hervor. Die Autoren beleuchten Kontext und materiellen Rechtsrahmen des Themas, auch unter Hervorhebung menschenrechtlicher Bezüge, institutionelles Recht („Gesundheit als Sicherheitsrisiko?“) sowie die Grenzen eines genuin rechtlichen Ansatzes. Die Autoren sind den Disziplinen Völkerrecht, Public Health, Politikwissenschaften und Anthropologie zuzuordnen. Mit Beiträgen von: Elif Askin, Susan L. Erikson, André den Exter, Robert Frau, Wolfgang Hein, Bonnie Kaiser, Hunter Keys, Michael Marx, Edefe Ojomo, Ilja Richard Pavone, Mateja Steinbrück Platise, Christian R. Thauer, Leonie Vierck, Pedro A. Villarreal, A. Katarina Weilert

LTL Parameter Synthesis of Parametric Timed Automata

The parameter synthesis problem for parametric timed automata is undecidable in general even for very simple reachability properties. In this paper we introduce restrictions on parameter valuations under which the parameter synthesis problem is decidable for LTL properties. The investigated bounded integer parameter synthesis problem could be solved using an explicit enumeration of all possible parameter valuations. We propose an alternative symbolic zone-based method for this problem which results in a faster computation. Our technique extends the ideas of the automata-based approach to LTL model checking of timed automata. To justify the usefulness of our approach, we provide experimental evaluation and compare our method with explicit enumeration technique.Comment: 23 pages, extended versio

A provably correct MPC approach to safety control of urban traffic networks

Model predictive control (MPC) is a popular strategy for urban traffic management that is able to incorporate physical and user defined constraints. However, the current MPC methods rely on finite horizon predictions that are unable to guarantee desirable behaviors over long periods of time. In this paper we design an MPC strategy that is guaranteed to keep the evolution of a network in a desirable yet arbitrary -safe- set, while optimizing a finite horizon cost function. Our approach relies on finding a robust controlled invariant set inside the safe set that provides an appropriate terminal constraint for the MPC optimization problem. An illustrative example is included.This work was partially supported by the NSF under grants CPS-1446151 and CMMI-1400167. (CPS-1446151 - NSF; CMMI-1400167 - NSF

Efficient parameter search for qualitative models of regulatory networks using symbolic model checking

Investigating the relation between the structure and behavior of complex biological networks often involves posing the following two questions: Is a hypothesized structure of a regulatory network consistent with the observed behavior? And can a proposed structure generate a desired behavior? Answering these questions presupposes that we are able to test the compatibility of network structure and behavior. We cast these questions into a parameter search problem for qualitative models of regulatory networks, in particular piecewise-affine differential equation models. We develop a method based on symbolic model checking that avoids enumerating all possible parametrizations, and show that this method performs well on real biological problems, using the IRMA synthetic network and benchmark experimental data sets. We test the consistency between the IRMA network structure and the time-series data, and search for parameter modifications that would improve the robustness of the external control of the system behavior