0000000000200698

AUTHOR

Simone Martini

Robust Network Agreement on Logical Information

Abstract Logical consensus is an approach to distributed decision making which is based on the availability of a network of agents with incomplete system knowledge. The method requires the construction of a Boolean map which defines a dynamic system allowing the entire network to consent on a unique, global decision. Previous work by the authors proved the method to be viable for applications such as intrusion detection within a structured environment, when the agent's communication topology is known in advance. The current work aims at providing a fully distributed protocol, requiring no a priori knowledge of each agent's communication neighbors. The protocol allows the construction of a r…

research product

Convergence Analysis of Distributed Set-Valued Information Systems

This paper focuses on the convergence of information in distributed systems of agents communicating over a network. The information on which the convergence is sought is not rep- resented by real numbers, as often in the literature, rather by sets. The dynamics of the evolution of information across the net- work is accordingly described by set-valued iterative maps. While the study of convergence of set-valued iterative maps is highly complex in general, this paper focuses on Boolean maps, which are comprised of arbitrary combinations of unions, intersections, and complements of sets. For these important class of systems, we provide tools to study both global and local convergence. A distr…

research product

Set-valued consensus for distributed clock synchronization

This paper addresses the clock synchronization problem in a wireless sensor network (WSN) and proposes a distributed solution that consists of a form of consensus, where agents are able to exchange data representing intervals or sets. The solution is based on a centralized algorithm for clock synchronization, proposed by Marzullo, that determines the smallest interval that is in common with the maximum number of measured intervals. We first show how to convert such an algorithm into a problem involving only operations on sets, and then we convert it into a set–valued consensus. The solution is valid for more general scenarios where agents have uncertain measures of e.g. the position of an o…

research product

Distributed Consensus on Boolean Information

Abstract In this paper we study the convergence towards consensus on information in a distributed system of agents communicating over a network. The particularity of this study is that the information on which the consensus is seeked is not represented by real numbers, rather by logical values or sets. Whereas the problems of allowing a network of agents to reach a consensus on logical functions of input events, and that of agreeing on set–valued information, have been separately addressed in previous work, in this paper we show that these problems can indeed be attacked in a unified way in the framework of Boolean distributed information systems. Based on a notion of contractivity for Bool…

research product

A self-routing protocol for distributed consensus on logical information

In this paper, we address decision making problems, depending on a set of input events, with networks of dynamic agents that have partial visibility of such events. Previous work by the authors proposed so-called logical consensus approach, by which a network of agents, that can exchange binary values representing their local estimates of the events, is able to reach a unique and consistent decision. The approach therein proposed is based on the construction of an iterative map, whose computation is centralized and guaranteed under suitable conditions on the input visibility and graph connectivity. Under the same conditions, we extend the approach in this work by allowing the construction o…

research product

Decentralized classification in societies of autonomous and heterogenous robots

This paper addresses the classification problem for a set of autonomous robots that interact with each other. The objective is to classify agents that “behave” in “different way”, due to their own physical dynamics or to the interaction protocol they are obeying to, as belonging to different “species”. This paper describes a technique that allows a decentralized classification system to be built in a systematic way, once the hybrid models describing the behavior of the different species are given. This technique is based on a decentralized identification mechanism, by which every agent classifies its neighbors using only local information. By endowing every agent with such a local classifie…

research product

Identification of Distributed Systems with Logical Interaction Structure

This paper focuses on the structure identification problem for a class of networked systems, where the interaction among components or agents is described through logical maps. In particular, agents are heterogeneous cooperating systems, i.e. they may have different individual dynamics and different interaction rules depending on input events. While we assume that the individual agents' dynamics are known, each agent has partial knowledge of the logical map encoding the interaction of another agent with its neighbors. Based on the so-called algebraic normal form for binary functions, we present a technique by which the network structure described by a logical function can be dynamically est…

research product