When Analysis Fails: Heuristic Mechanism Design via Self-Correcting Procedures

Computational mechanism design (CMD) seeks to understand how to design game forms that induce desirable outcomes in multi-agent systems despite private information, self-interest and limited computational resources. CMD finds application in many settings, in the public sector for wireless spectrum and airport landing rights, to Internet advertising, to expressive sourcing in the supply chain, to allocating computational resources. In meeting the demands for CMD in these rich domains, we often need to bridge from the theory of economic mechanism design to the practice of deployable, computational mechanisms. A compelling example of this need arises in dynamic combinatorial environments, where classic analytic approaches fail and heuristic, computational approaches are required. In this talk I outline the direction of self-correcting mechanisms, which dynamically modify decisions via “output ironing" to ensure truthfulness and provide a fully computational approach to mechanism design. For an application, I suggest heuristic mechanisms for dynamic auctions in which bids arrive over time and supply may also be uncertain.Engineering and Applied Science

Building Models through Formal Specification

Over the past years, a number of increasingly expressive languages for modelling constraint and optimisation problems have evolved. In developing a strategy to ease the complexity of building models for constraint and optimisation problems, we have asked ourselves whether, for modelling purposes, it is really necessary to introduce more new languages and notations. We have analyzed several emerging languages and formal notations and found (to our surprise) that the already existing Z notation, although not previously used in this context, proves to a high degree expressive, adaptable, and useful for the construction of problem models. To substantiate these claims, we have both compiled a large number of constraint and optimisation problems as formal Z specifications and translated models from a variety of constraint languages into Z. The results are available as an online library of model specifications, which we make openly available to the modelling community

Realtime Online Solving of Quantified CSPs

Abstract. We define Realtime Online solving of Quantified Constraint Satisfaction Problems (QCSPs) as a model for realtime online CSP solving. We use a combination of propagation, lookahead and heuristics and show how all three improve performance. For adversarial opponents we show that we can achieve promising results through good lookahead and heuristics and that a version of alpha beta pruning performs strongly. For random opponents, we show that we can frequently achieve solutions even on problems which lack a winning strategy and that we can improve our success rate by using Existential Quantified Generalised Arc Consistency, a lower level of consistency than SQGAC, to maximise pruning without removing solutions. We also consider the power of the universal opponent and show that through good heuristic selection we can generate a significantly stronger player than a static heuristic provides.

Generating propagators for finite set constraints

Abstract. Ideally, programming propagators as implementations of constraints should be an entirely declarative specification process for a large class of constraints: a high-level declarative specification is automatically translated into an efficient propagator. This paper introduces the use of existential monadic secondorder logic as declarative specification language for finite set propagators. The approach taken in the paper is to automatically derive projection propagators (involving a single variable only) implementing constraints described by formulas. By this, the paper transfers the ideas of indexicals to finite set constraints while considerably increasing the level of abstraction available with indexicals. The paper proves soundness and completeness of the derived propagators and presents a run-time analysis, including techniques for efficiently executing projectors for n-ary constraints.

Experiments in Parallel Constraint-Based Local Search

International audienceWe present a parallel implementation of a constraint-based local search algorithm and investigate its performance results on hardware with several hundreds of processors. We choose as basic constraint solving algorithm for these experiments the "adaptive search" method, an efficient sequential local search method for Constraint Satisfaction Problems. The implemented algorithm is a parallel version of adaptive search in a multiple independent-walk manner, that is, each process is an independent search engine and there is no communication between the simultaneous computations. Preliminary performance evaluation on a variety of classical CSPs benchmarks shows that speedups are very good for a few tens of processors, and good up to a few hundreds of processors

Canonical dual least square method for solving general nonlinear systems of quadratic equations

Duality theory, Nonlinear systems of equations, Global optimization, Least square method,

Metaheuristic Hybrids

International audienc