An Axiomatic Approach to Routing

Information delivery in a network of agents is a key issue for large, complex systems that need to do so in a predictable, efficient manner. The delivery of information in such multi-agent systems is typically implemented through routing protocols that determine how information flows through the network. Different routing protocols exist each with its own benefits, but it is generally unclear which properties can be successfully combined within a given algorithm. We approach this problem from the axiomatic point of view, i.e., we try to establish what are the properties we would seek to see in such a system, and examine the different properties which uniquely define common routing algorithms used today. We examine several desirable properties, such as robustness, which ensures adding nodes and edges does not change the routing in a radical, unpredictable ways; and properties that depend on the operating environment, such as an "economic model", where nodes choose their paths based on the cost they are charged to pass information to the next node. We proceed to fully characterize minimal spanning tree, shortest path, and weakest link routing algorithms, showing a tight set of axioms for each.Comment: In Proceedings TARK 2015, arXiv:1606.0729

Distributed Computing with Adaptive Heuristics

We use ideas from distributed computing to study dynamic environments in which computational nodes, or decision makers, follow adaptive heuristics (Hart 2005), i.e., simple and unsophisticated rules of behavior, e.g., repeatedly "best replying" to others' actions, and minimizing "regret", that have been extensively studied in game theory and economics. We explore when convergence of such simple dynamics to an equilibrium is guaranteed in asynchronous computational environments, where nodes can act at any time. Our research agenda, distributed computing with adaptive heuristics, lies on the borderline of computer science (including distributed computing and learning) and game theory (including game dynamics and adaptive heuristics). We exhibit a general non-termination result for a broad class of heuristics with bounded recall---that is, simple rules of behavior that depend only on recent history of interaction between nodes. We consider implications of our result across a wide variety of interesting and timely applications: game theory, circuit design, social networks, routing and congestion control. We also study the computational and communication complexity of asynchronous dynamics and present some basic observations regarding the effects of asynchrony on no-regret dynamics. We believe that our work opens a new avenue for research in both distributed computing and game theory.Comment: 36 pages, four figures. Expands both technical results and discussion of v1. Revised version will appear in the proceedings of Innovations in Computer Science 201

Evaluating health effects of transport interventions: methodologic case study

Background: There is little evidence about the effects of environmental interventions on population levels of physical activity. Major transport projects may promote or discourage physical activity in the form of walking and cycling, but researching the health effects of such “natural experiments” in transport policy or infrastructure is challenging. Methods: Case study of attempts in 2004–2005 to evaluate the effects of two major transport projects in Scotland: an urban congestion charging scheme in Edinburgh, and a new urban motorway (freeway) in Glasgow. Results: These interventions are typical of many major transport projects. They are unique to their context. They cannot easily be separated from the other components of the wider policies within which they occur. When, where, and how they are implemented are political decisions over which researchers have no control. Baseline data collection required for longitudinal studies may need to be planned before the intervention is certain to take place. There is no simple way of defining a population or area exposed to the intervention or of defining control groups. Changes in quantitative measures of health-related behavior may be difficult to detect. Conclusions: Major transport projects have clear potential to influence population health, but it is difficult to define the interventions, categorize exposure, or measure outcomes in ways that are likely to be seen as credible in the field of public health intervention research. A final study design is proposed in which multiple methods and spatial levels of analysis are combined in a longitudinal quasi-experimental study

A Tracing Method for Pricing Inter-Area Electricity Trades

In the context of liberalisation of electricity markets world wide, the need for agreed protocols for electricity trades between systems with different charges poses a special challenge. System operators need to know how much a given trade uses the network, in order to allocate an appropriate portion of their costs to that trade. This paper discusses a technique, tracing, for determining how much each of a number of trades uses different parts of the electricity network. The scheme is based on the assumption that at any network node, inflows are shared proportionally between outflows (and vice versa). The paper outlines the technique and shows how it could be applied to the problem of charging cross-border trades. The paper goes on to demonstrate that the technique has a game theoretic rationale, in that it produces the Shapley value solution to a game equivalent to this allocation problem

Homo Datumicus : correcting the market for identity data

Effective digital identity systems offer great economic and civic potential. However, unlocking this potential requires dealing with social, behavioural, and structural challenges to efficient market formation. We propose that a marketplace for identity data can be more efficiently formed with an infrastructure that provides a more adequate representation of individuals online. This paper therefore introduces the ontological concept of Homo Datumicus: individuals as data subjects transformed by HAT Microservers, with the axiomatic computational capabilities to transact with their own data at scale. Adoption of this paradigm would lower the social risks of identity orientation, enable privacy preserving transactions by default and mitigate the risks of power imbalances in digital identity systems and markets

Solving congestion (when we must not build roads, increase spending, lose votes, damage the economy or harm the environment, and will never find equilibrium)

An account of the development of transport and traffic policy over the last 30 years, with suggestions for the future constraints and objective

Back to the Future: Economic Self-Organisation and Maximum Entropy Prediction

This paper shows that signal restoration methodology is appropriate for predicting the equilibrium state of certain economic systems. A formal justification for this is provided by proving the existence of finite improvement paths in object allocation problems under weak assumptions on preferences, linking any initial condition to a Nash equilibrium. Because a finite improvement path is made up of a sequence of systematic best-responses, backwards movement from the equilibrium back to the initial condition can be treated like the realisation of a noise process. This underpins the use of signal restoration to predict the equilibrium from the initial condition, and an illustration is provided through an application of maximum entropy signal restoration to the Schelling model of segregation