7 research outputs found
Courtesy as a Means to Coordinate
We investigate the problem of multi-agent coordination under rationality
constraints. Specifically, role allocation, task assignment, resource
allocation, etc. Inspired by human behavior, we propose a framework (CA^3NONY)
that enables fast convergence to efficient and fair allocations based on a
simple convention of courtesy. We prove that following such convention induces
a strategy which constitutes an -subgame-perfect equilibrium of the
repeated allocation game with discounting. Simulation results highlight the
effectiveness of CA^3NONY as compared to state-of-the-art bandit algorithms,
since it achieves more than two orders of magnitude faster convergence, higher
efficiency, fairness, and average payoff.Comment: Accepted at AAMAS 2019 (International Conference on Autonomous Agents
and Multiagent Systems
Beyond the echo chamber:Modelling open-mindedness in citizensâ assemblies
A Citizensâ assembly (CA) is a democratic innovation tool where a randomly selected group of citizens deliberate a topic over multiple rounds to generate, and then vote upon, policy recommendations. Despite growing popularity, little work exists on understanding how CA inputs, such as the expert selection process and the mixing method used for discussion groups, affect results. In this work, we model CA deliberation and opinion change as a multi-agent systems problem. We introduce and formalise a set of criteria for evaluating successful CAs using insight from previous CA trials and theoretical results. Although real-world trials meet these criteria, we show that finding a model that does so is non-trivial; through simulations and theoretical arguments, we show that established opinion change models fail at least one of these criteria. We therefore propose an augmented opinion change model with a latent âopen-mindednessâ variable, which sufficiently captures peopleâs propensity to change opinion. We show that data from the CA of Scotland indicates a latent variable both exists and resembles the concept of open-mindedness in the literature. We calibrate parameters against real CA data, demonstrating our modelâs ecological validity, before running simulations across a range of realistic global parameters, with each simulation satisfying our criteria. Specifically, simulations meet criteria regardless of expert selection, expert ordering, participant extremism, and sub-optimal participant grouping, which has ramifications for optimised algorithmic approaches in the computational CA space