7,214 research outputs found
Prompt Delay
Delay games are two-player games of infinite duration in which one player may
delay her moves to obtain a lookahead on her opponent's moves. Recently, such
games with quantitative winning conditions in weak MSO with the unbounding
quantifier were studied, but their properties turned out to be unsatisfactory.
In particular, unbounded lookahead is in general necessary. Here, we study
delay games with winning conditions given by Prompt-LTL, Linear Temporal Logic
equipped with a parameterized eventually operator whose scope is bounded. Our
main result shows that solving Prompt-LTL delay games is complete for
triply-exponential time. Furthermore, we give tight triply-exponential bounds
on the necessary lookahead and on the scope of the parameterized eventually
operator. Thus, we identify Prompt-LTL as the first known class of well-behaved
quantitative winning conditions for delay games. Finally, we show that applying
our techniques to delay games with \omega-regular winning conditions answers
open questions in the cases where the winning conditions are given by
non-deterministic, universal, or alternating automata
Strong games played on random graphs
In a strong game played on the edge set of a graph G there are two players,
Red and Blue, alternating turns in claiming previously unclaimed edges of G
(with Red playing first). The winner is the first one to claim all the edges of
some target structure (such as a clique, a perfect matching, a Hamilton cycle,
etc.). It is well known that Red can always ensure at least a draw in any
strong game, but finding explicit winning strategies is a difficult and a quite
rare task. We consider strong games played on the edge set of a random graph G
~ G(n,p) on n vertices. We prove, for sufficiently large and a fixed
constant 0 < p < 1, that Red can w.h.p win the perfect matching game on a
random graph G ~ G(n,p)
Adaptive Nonparametric Image Parsing
In this paper, we present an adaptive nonparametric solution to the image
parsing task, namely annotating each image pixel with its corresponding
category label. For a given test image, first, a locality-aware retrieval set
is extracted from the training data based on super-pixel matching similarities,
which are augmented with feature extraction for better differentiation of local
super-pixels. Then, the category of each super-pixel is initialized by the
majority vote of the -nearest-neighbor super-pixels in the retrieval set.
Instead of fixing as in traditional non-parametric approaches, here we
propose a novel adaptive nonparametric approach which determines the
sample-specific k for each test image. In particular, is adaptively set to
be the number of the fewest nearest super-pixels which the images in the
retrieval set can use to get the best category prediction. Finally, the initial
super-pixel labels are further refined by contextual smoothing. Extensive
experiments on challenging datasets demonstrate the superiority of the new
solution over other state-of-the-art nonparametric solutions.Comment: 11 page
A Grey-Box Approach to Automated Mechanism Design
Auctions play an important role in electronic commerce, and have been used to
solve problems in distributed computing. Automated approaches to designing
effective auction mechanisms are helpful in reducing the burden of traditional
game theoretic, analytic approaches and in searching through the large space of
possible auction mechanisms. This paper presents an approach to automated
mechanism design (AMD) in the domain of double auctions. We describe a novel
parametrized space of double auctions, and then introduce an evolutionary
search method that searches this space of parameters. The approach evaluates
auction mechanisms using the framework of the TAC Market Design Game and
relates the performance of the markets in that game to their constituent parts
using reinforcement learning. Experiments show that the strongest mechanisms we
found using this approach not only win the Market Design Game against known,
strong opponents, but also exhibit desirable economic properties when they run
in isolation.Comment: 18 pages, 2 figures, 2 tables, and 1 algorithm. Extended abstract to
appear in the proceedings of AAMAS'201
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