3,957 research outputs found
Online Distributed Sensor Selection
A key problem in sensor networks is to decide which sensors to query when, in
order to obtain the most useful information (e.g., for performing accurate
prediction), subject to constraints (e.g., on power and bandwidth). In many
applications the utility function is not known a priori, must be learned from
data, and can even change over time. Furthermore for large sensor networks
solving a centralized optimization problem to select sensors is not feasible,
and thus we seek a fully distributed solution. In this paper, we present
Distributed Online Greedy (DOG), an efficient, distributed algorithm for
repeatedly selecting sensors online, only receiving feedback about the utility
of the selected sensors. We prove very strong theoretical no-regret guarantees
that apply whenever the (unknown) utility function satisfies a natural
diminishing returns property called submodularity. Our algorithm has extremely
low communication requirements, and scales well to large sensor deployments. We
extend DOG to allow observation-dependent sensor selection. We empirically
demonstrate the effectiveness of our algorithm on several real-world sensing
tasks
Complexity Theory, Game Theory, and Economics: The Barbados Lectures
This document collects the lecture notes from my mini-course "Complexity
Theory, Game Theory, and Economics," taught at the Bellairs Research Institute
of McGill University, Holetown, Barbados, February 19--23, 2017, as the 29th
McGill Invitational Workshop on Computational Complexity.
The goal of this mini-course is twofold: (i) to explain how complexity theory
has helped illuminate several barriers in economics and game theory; and (ii)
to illustrate how game-theoretic questions have led to new and interesting
complexity theory, including recent several breakthroughs. It consists of two
five-lecture sequences: the Solar Lectures, focusing on the communication and
computational complexity of computing equilibria; and the Lunar Lectures,
focusing on applications of complexity theory in game theory and economics. No
background in game theory is assumed.Comment: Revised v2 from December 2019 corrects some errors in and adds some
recent citations to v1 Revised v3 corrects a few typos in v
Empirical Centroid Fictitious Play: An Approach For Distributed Learning In Multi-Agent Games
The paper is concerned with distributed learning in large-scale games. The
well-known fictitious play (FP) algorithm is addressed, which, despite
theoretical convergence results, might be impractical to implement in
large-scale settings due to intense computation and communication requirements.
An adaptation of the FP algorithm, designated as the empirical centroid
fictitious play (ECFP), is presented. In ECFP players respond to the centroid
of all players' actions rather than track and respond to the individual actions
of every player. Convergence of the ECFP algorithm in terms of average
empirical frequency (a notion made precise in the paper) to a subset of the
Nash equilibria is proven under the assumption that the game is a potential
game with permutation invariant potential function. A more general formulation
of ECFP is then given (which subsumes FP as a special case) and convergence
results are given for the class of potential games. Furthermore, a distributed
formulation of the ECFP algorithm is presented, in which, players endowed with
a (possibly sparse) preassigned communication graph, engage in local,
non-strategic information exchange to eventually agree on a common equilibrium.
Convergence results are proven for the distributed ECFP algorithm.Comment: Submitted to the IEEE Transactions on Signal Processin
First-principle molecular dynamics with ultrasoft pseudopotentials: parallel implementation and application to extended bio-inorganic system
We present a plane-wave ultrasoft pseudopotential implementation of
first-principle molecular dynamics, which is well suited to model large
molecular systems containing transition metal centers. We describe an efficient
strategy for parallelization that includes special features to deal with the
augmented charge in the contest of Vanderbilt's ultrasoft pseudopotentials. We
also discuss a simple approach to model molecular systems with a net charge
and/or large dipole/quadrupole moments. We present test applications to
manganese and iron porphyrins representative of a large class of biologically
relevant metallorganic systems. Our results show that accurate
Density-Functional Theory calculations on systems with several hundred atoms
are feasible with access to moderate computational resources.Comment: 29 pages, 4 Postscript figures, revtex
- …