Trust and distrust in contradictory information transmission

We analyse the problem of contradictory information distribution in networks of agents with positive and negative trust. The networks of interest are built by ranked agents with different epistemic attitudes. In this context, positive trust is a property of the communication between agents required when message passing is executed bottom-up in the hierarchy, or as a result of a sceptic agent checking information. These two situations are associated with a confirmation procedure that has an epistemic cost. Negative trust results from refusing verification, either of contradictory information or because of a lazy attitude. We offer first a natural deduction system called SecureNDsim to model these interactions and consider some meta-theoretical properties of its derivations. We then implement it in a NetLogo simulation to test experimentally its formal properties. Our analysis concerns in particular: conditions for consensus-reaching transmissions; epistemic costs induced by confirmation and rejection operations; the influence of ranking of the initially labelled nodes on consensus and costs; complexity results

Trust and distrust in contradictory information transmission

We analyse the problem of contradictory information distribution in networks of agents with positive and negative trust. The networks of interest are built by ranked agents with different epistemic attitudes. In this context, positive trust is a property of the communication between agents required when message passing is executed bottom-up in the hierarchy, or as a result of a sceptic agent checking information. These two situations are associated with a confirmation procedure that has an epistemic cost. Negative trust results from refusing verification, either of contradictory information or because of a lazy attitude. We offer first a natural deduction system called SecureNDsim to model these interactions and consider some meta-theoretical properties of its derivations. We then implement it in a NetLogo simulation to test experimentally its formal properties. Our analysis concerns in particular: conditions for consensus-reaching transmissions; epistemic costs induced by confirmation and rejection operations; the influence of ranking of the initially labelled nodes on consensus and costs; complexity results

Contradictory information flow in networks with trust and distrust

We offer a proof system and a NetLogo simulation for trust and distrust in networks where contradictory information is shared by ranked lazy and sceptic agents. Trust and its negative are defined as properties of edges: the former is required when a message is passed bottom-up in the hierarchy or received by a sceptic agent; the latter is attributed to channels that require contradiction resolution, or whose terminal is a lazy agent. These procedures are associated with epistemic costs, respectively for confirmation and refutation. We describe the logic, illustrate the algorithms implemented in the model and then focus on experimental results concerning the analysis of epistemic costs, the role of the agents’ epistemic attitude on distrust distribution and the influence of (dis)trust in reaching consensus

Contradictory information flow in networks with trust and distrust

We offer a proof system and a NetLogo simulation for trust and distrust in networks where contradictory information is shared by ranked lazy and sceptic agents. Trust and its negative are defined as properties of edges: the former is required when a message is passed bottom-up in the hierarchy or received by a sceptic agent; the latter is attributed to channels that require contradiction resolution, or whose terminal is a lazy agent. These procedures are associated with epistemic costs, respectively for confirmation and refutation. We describe the logic, illustrate the algorithms implemented in the model and then focus on experimental results concerning the analysis of epistemic costs, the role of the agents’ epistemic attitude on distrust distribution and the influence of (dis)trust in reaching consensus

Agoric computation: trust and cyber-physical systems

In the past two decades advances in miniaturisation and economies of scale have led to the emergence of billions of connected components that have provided both a spur and a blueprint for the development of smart products acting in specialised environments which are uniquely identifiable, localisable, and capable of autonomy. Adopting the computational perspective of multi-agent systems (MAS) as a technological abstraction married with the engineering perspective of cyber-physical systems (CPS) has provided fertile ground for designing, developing and deploying software applications in smart automated context such as manufacturing, power grids, avionics, healthcare and logistics, capable of being decentralised, intelligent, reconfigurable, modular, flexible, robust, adaptive and responsive. Current agent technologies are, however, ill suited for information-based environments, making it difficult to formalise and implement multiagent systems based on inherently dynamical functional concepts such as trust and reliability, which present special challenges when scaling from small to large systems of agents. To overcome such challenges, it is useful to adopt a unified approach which we term agoric computation, integrating logical, mathematical and programming concepts towards the development of agent-based solutions based on recursive, compositional principles, where smaller systems feed via directed information flows into larger hierarchical systems that define their global environment. Considering information as an integral part of the environment naturally defines a web of operations where components of a systems are wired in some way and each set of inputs and outputs are allowed to carry some value. These operations are stateless abstractions and procedures that act on some stateful cells that cumulate partial information, and it is possible to compose such abstractions into higher-level ones, using a publish-and-subscribe interaction model that keeps track of update messages between abstractions and values in the data. In this thesis we review the logical and mathematical basis of such abstractions and take steps towards the software implementation of agoric modelling as a framework for simulation and verification of the reliability of increasingly complex systems, and report on experimental results related to a few select applications, such as stigmergic interaction in mobile robotics, integrating raw data into agent perceptions, trust and trustworthiness in orchestrated open systems, computing the epistemic cost of trust when reasoning in networks of agents seeded with contradictory information, and trust models for distributed ledgers in the Internet of Things (IoT); and provide a roadmap for future developments of our research

A logic of negative trust

We present a logic to model the behaviour of an agent trusting or not trusting messages sent by another agent. The logic formalises trust as a consistency checking function with respect to currently available information. Negative trust is modelled in two forms: distrust, as the rejection of incoming inconsistent information; mistrust, as revision of previously held information becoming undesirable in view of new incoming inconsistent information, which the agent wishes to accept. We provide a natural deduction calculus, a relational semantics and prove soundness and completeness results. We overview a number of applications which have been investigated for the proof-theoretical formulation of the logic

A "superstorm": When moral panic and new risk discourses converge in the media

This is an Author's Accepted Manuscript of an article published in Health, Risk and Society, 15(6), 681-698, 2013, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/13698575.2013.851180.There has been a proliferation of risk discourses in recent decades but studies of these have been polarised, drawing either on moral panic or new risk frameworks to analyse journalistic discourses. This article opens the theoretical possibility that the two may co-exist and converge in the same scare. I do this by bringing together more recent developments in moral panic thesis, with new risk theory and the concept of media logic. I then apply this theoretical approach to an empirical analysis of how and with what consequences moral panic and new risk type discourses converged in the editorials of four newspaper campaigns against GM food policy in Britain in the late 1990s. The article analyses 112 editorials published between January 1998 and December 2000, supplemented with news stories where these were needed for contextual clarity. This analysis shows that not only did this novel food generate intense media and public reactions; these developed in the absence of the type of concrete details journalists usually look for in risk stories. Media logic is important in understanding how journalists were able to engage and hence how a major scare could be constructed around convergent moral panic and new risk type discourses. The result was a media ‘superstorm’ of sustained coverage in which both types of discourse converged in highly emotive mutually reinforcing ways that resonated in a highly sensitised context. The consequence was acute anxiety, social volatility and the potential for the disruption of policy and social change

A calculus for distrust and mistrust

Properties of trust are becoming widely studied in several applications within the computational domain. On the contrary, negative trust attribution is less well-defined and related issues are yet to be approached and resolved. We present a natural deduction calculus for trust protocols and its negative forms, distrust and mistrust. The calculus deals efficiently with forms of trust transitivity and negative trust multiplication and we briefly illustrate some possible applications

A calculus for distrust and mistrust

Properties of trust are becoming widely studied in several applications within the computational domain. On the contrary, negative trust attribution is less well-defined and related issues are yet to be approached and resolved. We present a natural deduction calculus for trust protocols and its negative forms, distrust and mistrust. The calculus deals efficiently with forms of trust transitivity and negative trust multiplication and we briefly illustrate some possible applications