10,744 research outputs found
Decision Making under Uncertainty: Revealing, Characterizing and Modeling Individual Differences in the Iowa Gambling Task.
Decision making, the process of choosing among a set of options, is a fundamental aspect of everyday mental life. Decisions are often made under conditions of uncertainty, when the payoffs are probabilistic and unknown. Two important challenges in the study of decision making are to understand how decision making processes are instantiated computationally and to reveal and characterize differences in decision making processes across individuals. In this dissertation I used computational and behavioral methods to study decision making under uncertainty in the context of the Iowa Gambling Task (IGT). The main contributions are: (i) A biologically-grounded computational model that provides a better account of IGT behavior than the most widely accepted model; (ii) The identification of three fundamentally different decision making styles in the IGT; (iii) An improved conceptualization of decision making that offers a more comprehensive approach to analyzing performance and that has important implications for the study of normal and clinically impaired decision making; (iv) An empirical challenge to the widely held belief that IGT performance is associated with impulsive and risky decision making; (v) A demonstrated association between decision making in the IGT and cognitive abilities as measured by the Wisconsin Card Sorting Task; and (vi) the introduction and successful demonstration of a robust data clustering methodology that offers significant advantages over methods that are currently used in the field of Psychology.Ph.D.Computer Science and Engineering and PsychologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64780/1/leenewm_1.pd
Sign-time distributions for interface growth
We apply the recently introduced distribution of sign-times (DST) to
non-equilibrium interface growth dynamics. We are able to treat within a
unified picture the persistence properties of a large class of relaxational and
noisy linear growth processes, and prove the existence of a non-trivial scaling
relation. A new critical dimension is found, relating to the persistence
properties of these systems. We also illustrate, by means of numerical
simulations, the different types of DST to be expected in both linear and
non-linear growth mechanisms.Comment: 4 pages, 5 ps figs, replaced misprint in authors nam
Sandpiles on multiplex networks
We introduce the sandpile model on multiplex networks with more than one type
of edge and investigate its scaling and dynamical behaviors. We find that the
introduction of multiplexity does not alter the scaling behavior of avalanche
dynamics; the system is critical with an asymptotic power-law avalanche size
distribution with an exponent on duplex random networks. The
detailed cascade dynamics, however, is affected by the multiplex coupling. For
example, higher-degree nodes such as hubs in scale-free networks fail more
often in the multiplex dynamics than in the simplex network counterpart in
which different types of edges are simply aggregated. Our results suggest that
multiplex modeling would be necessary in order to gain a better understanding
of cascading failure phenomena of real-world multiplex complex systems, such as
the global economic crisis.Comment: 7 pages, 7 figure
On the optimality of gluing over scales
We show that for every , there exist -point metric spaces
(X,d) where every "scale" admits a Euclidean embedding with distortion at most
, but the whole space requires distortion at least . This shows that the scale-gluing lemma [Lee, SODA 2005] is tight,
and disproves a conjecture stated there. This matching upper bound was known to
be tight at both endpoints, i.e. when and , but nowhere in between.
More specifically, we exhibit -point spaces with doubling constant
requiring Euclidean distortion ,
which also shows that the technique of "measured descent" [Krauthgamer, et.
al., Geometric and Functional Analysis] is optimal. We extend this to obtain a
similar tight result for spaces with .Comment: minor revision
Complete trails of co-authorship network evolution
The rise and fall of a research field is the cumulative outcome of its
intrinsic scientific value and social coordination among scientists. The
structure of the social component is quantifiable by the social network of
researchers linked via co-authorship relations, which can be tracked through
digital records. Here, we use such co-authorship data in theoretical physics
and study their complete evolutionary trail since inception, with a particular
emphasis on the early transient stages. We find that the co-authorship networks
evolve through three common major processes in time: the nucleation of small
isolated components, the formation of a tree-like giant component through
cluster aggregation, and the entanglement of the network by large-scale loops.
The giant component is constantly changing yet robust upon link degradations,
forming the network's dynamic core. The observed patterns are successfully
reproducible through a new network model
Evolution of scale-free random graphs: Potts model formulation
We study the bond percolation problem in random graphs of weighted
vertices, where each vertex has a prescribed weight and an edge can
connect vertices and with rate . The problem is solved by the
limit of the -state Potts model with inhomogeneous interactions for
all pairs of spins. We apply this approach to the static model having
so that the resulting graph is scale-free with
the degree exponent . The number of loops as well as the giant
cluster size and the mean cluster size are obtained in the thermodynamic limit
as a function of the edge density, and their associated critical exponents are
also obtained. Finite-size scaling behaviors are derived using the largest
cluster size in the critical regime, which is calculated from the cluster size
distribution, and checked against numerical simulation results. We find that
the process of forming the giant cluster is qualitatively different between the
cases of and . While for the former, the giant
cluster forms abruptly at the percolation transition, for the latter, however,
the formation of the giant cluster is gradual and the mean cluster size for
finite shows double peaks.Comment: 34 pages, 9 figures, elsart.cls, final version appeared in NP
Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines
Researchers' networks have been subject to active modeling and analysis.
Earlier literature mostly focused on citation or co-authorship networks
reconstructed from annotated scientific publication databases, which have
several limitations. Recently, general-purpose web search engines have also
been utilized to collect information about social networks. Here we
reconstructed, using web search engines, a network representing the relatedness
of researchers to their peers as well as to various research topics.
Relatedness between researchers and research topics was characterized by
visibility boost-increase of a researcher's visibility by focusing on a
particular topic. It was observed that researchers who had high visibility
boosts by the same research topic tended to be close to each other in their
network. We calculated correlations between visibility boosts by research
topics and researchers' interdisciplinarity at individual level (diversity of
topics related to the researcher) and at social level (his/her centrality in
the researchers' network). We found that visibility boosts by certain research
topics were positively correlated with researchers' individual-level
interdisciplinarity despite their negative correlations with the general
popularity of researchers. It was also found that visibility boosts by
network-related topics had positive correlations with researchers' social-level
interdisciplinarity. Research topics' correlations with researchers'
individual- and social-level interdisciplinarities were found to be nearly
independent from each other. These findings suggest that the notion of
"interdisciplinarity" of a researcher should be understood as a
multi-dimensional concept that should be evaluated using multiple assessment
means.Comment: 20 pages, 7 figures. Accepted for publication in PLoS On
Classical and quantum partition bound and detector inefficiency
We study randomized and quantum efficiency lower bounds in communication
complexity. These arise from the study of zero-communication protocols in which
players are allowed to abort. Our scenario is inspired by the physics setup of
Bell experiments, where two players share a predefined entangled state but are
not allowed to communicate. Each is given a measurement as input, which they
perform on their share of the system. The outcomes of the measurements should
follow a distribution predicted by quantum mechanics; however, in practice, the
detectors may fail to produce an output in some of the runs. The efficiency of
the experiment is the probability that the experiment succeeds (neither of the
detectors fails).
When the players share a quantum state, this gives rise to a new bound on
quantum communication complexity (eff*) that subsumes the factorization norm.
When players share randomness instead of a quantum state, the efficiency bound
(eff), coincides with the partition bound of Jain and Klauck. This is one of
the strongest lower bounds known for randomized communication complexity, which
subsumes all the known combinatorial and algebraic methods including the
rectangle (corruption) bound, the factorization norm, and discrepancy.
The lower bound is formulated as a convex optimization problem. In practice,
the dual form is more feasible to use, and we show that it amounts to
constructing an explicit Bell inequality (for eff) or Tsirelson inequality (for
eff*). We give an example of a quantum distribution where the violation can be
exponentially bigger than the previously studied class of normalized Bell
inequalities.
For one-way communication, we show that the quantum one-way partition bound
is tight for classical communication with shared entanglement up to arbitrarily
small error.Comment: 21 pages, extended versio
Entropy-based analysis of the number partitioning problem
In this paper we apply the multicanonical method of statistical physics on
the number-partitioning problem (NPP). This problem is a basic NP-hard problem
from computer science, and can be formulated as a spin-glass problem. We
compute the spectral degeneracy, which gives us information about the number of
solutions for a given cost and cardinality . We also study an extension
of this problem for partitions. We show that a fundamental difference on
the spectral degeneracy of the generalized () NPP exists, which could
explain why it is so difficult to find good solutions for this case. The
information obtained with the multicanonical method can be very useful on the
construction of new algorithms.Comment: 6 pages, 4 figure
Critical phenomena in complex networks
The combination of the compactness of networks, featuring small diameters,
and their complex architectures results in a variety of critical effects
dramatically different from those in cooperative systems on lattices. In the
last few years, researchers have made important steps toward understanding the
qualitatively new critical phenomena in complex networks. We review the
results, concepts, and methods of this rapidly developing field. Here we mostly
consider two closely related classes of these critical phenomena, namely
structural phase transitions in the network architectures and transitions in
cooperative models on networks as substrates. We also discuss systems where a
network and interacting agents on it influence each other. We overview a wide
range of critical phenomena in equilibrium and growing networks including the
birth of the giant connected component, percolation, k-core percolation,
phenomena near epidemic thresholds, condensation transitions, critical
phenomena in spin models placed on networks, synchronization, and
self-organized criticality effects in interacting systems on networks. We also
discuss strong finite size effects in these systems and highlight open problems
and perspectives.Comment: Review article, 79 pages, 43 figures, 1 table, 508 references,
extende
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