Timing and Virtual Observability in Ultimatum Bargaining and "Weak Link" Coordination Games

Previous studies have shown that simply knowing one player moves first can affect behavior in games, even when the first-mover's moves are known to be unobservable. This observation violates the game-theoretic principle that timing of unobserved moves is irrelevant, but is consistent with virtual observability, a theory of how timing can matter without the ability to observe actions. However, this previous research only shows that timing matters in games where knowledge that one player moved first can help select that player's preferred equilibrium, presenting an alternative explanation to virtual observability. We extend this work by varying timing of unobservable moves in ultimatum bargaining games and “weak link” coordination games. In the latter, the equilibrium selection explanation does not predict any change in behavior due to timing differences. We find that timing without observability affects behavior in both games, but not substantially

Staggered local density-of-states around the vortex in underdoped cuprates

We have studied a single vortex with the staggered flux (SF) core based on the SU(2) slave-boson theory of high $T_c$ superconductors. We find that whereas the center in the vortex core is a SF state, as one moves away from the core center, a correlated staggered modulation of the hopping amplitude $\chi$ and pairing amplitude $\Delta$ becomes predominant. We predict that in this region, the local density-of-states (LDOS) exhibits staggered modulation when measured on the bonds, which may be directly detected by STM experiments.Comment: 4 pages, 3 figure

Unsupervised Discovery of Parts, Structure, and Dynamics

Humans easily recognize object parts and their hierarchical structure by watching how they move; they can then predict how each part moves in the future. In this paper, we propose a novel formulation that simultaneously learns a hierarchical, disentangled object representation and a dynamics model for object parts from unlabeled videos. Our Parts, Structure, and Dynamics (PSD) model learns to, first, recognize the object parts via a layered image representation; second, predict hierarchy via a structural descriptor that composes low-level concepts into a hierarchical structure; and third, model the system dynamics by predicting the future. Experiments on multiple real and synthetic datasets demonstrate that our PSD model works well on all three tasks: segmenting object parts, building their hierarchical structure, and capturing their motion distributions.Comment: ICLR 2019. The first two authors contributed equally to this wor

Treatment of Epsilon-Moves in Subset Construction

The paper discusses the problem of determinising finite-state automata containing large numbers of epsilon-moves. Experiments with finite-state approximations of natural language grammars often give rise to very large automata with a very large number of epsilon-moves. The paper identifies three subset construction algorithms which treat epsilon-moves. A number of experiments has been performed which indicate that the algorithms differ considerably in practice. Furthermore, the experiments suggest that the average number of epsilon-moves per state can be used to predict which algorithm is likely to perform best for a given input automaton

Residential Mobility During Adolescence: Even Upward Moves Predict High School Dropout

Racial and economic segregation have long endured as systemic challenges in U.S. metropolitan areas. To combat the inequalities of segregation, two broad policy approaches have emerged: (1) preservation stresses investment in low-income neighborhoods, and (2) mobility stresses moving households in low-income areas to more affluent areas. Our recent study reveals some possible unintended consequences of the latter approach, particularly for adolescents. We find that moving during adolescence is associated with decreased odds of graduating from high school, even when moving to significantly higher income neighborhoods

Computational investigations of folded self-avoiding walks related to protein folding

Various subsets of self-avoiding walks naturally appear when investigating existing methods designed to predict the 3D conformation of a protein of interest. Two such subsets, namely the folded and the unfoldable self-avoiding walks, are studied computationally in this article. We show that these two sets are equal and correspond to the whole $n$-step self-avoiding walks for $n\leqslant 14$, but that they are different for numerous $n \geqslant 108$, which are common protein lengths. Concrete counterexamples are provided and the computational methods used to discover them are completely detailed. A tool for studying these subsets of walks related to both pivot moves and proteins conformations is finally presented.Comment: Not yet submitte

Prediction Possibility in the Fractal Overlap Model of Earthquakes

The two-fractal overlap model of earthquake shows that the contact area distribution of two fractal surfaces follows power law decay in many cases and this agrees with the Guttenberg-Richter power law. Here, we attempt to predict the large events (earthquakes) in this model through the overlap time-series analysis. Taking only the Cantor sets, the overlap sizes (contact areas) are noted when one Cantor set moves over the other with uniform velocity. This gives a time series containing different overlap sizes. Our numerical study here shows that the cumulative overlap size grows almost linearly with time and when the overlapsizes are added up to a pre-assigned large event (earthquake) and then reset to `zero' level, the corresponding cumulative overlap sizes grows upto some discrete (quantised) levels. This observation should help to predict the possibility of `large events' in this (overlap) time series.Comment: 6 pages, 6 figures. To be published as proc. NATO conf. CMDS-10, Soresh, Israel, July 2003. Eds. D. J. Bergman & E. Inan, KLUWER PUB