2,320 research outputs found
Collective Intelligence for Control of Distributed Dynamical Systems
We consider the El Farol bar problem, also known as the minority game (W. B.
Arthur, ``The American Economic Review'', 84(2): 406--411 (1994), D. Challet
and Y.C. Zhang, ``Physica A'', 256:514 (1998)). We view it as an instance of
the general problem of how to configure the nodal elements of a distributed
dynamical system so that they do not ``work at cross purposes'', in that their
collective dynamics avoids frustration and thereby achieves a provided global
goal. We summarize a mathematical theory for such configuration applicable when
(as in the bar problem) the global goal can be expressed as minimizing a global
energy function and the nodes can be expressed as minimizers of local free
energy functions. We show that a system designed with that theory performs
nearly optimally for the bar problem.Comment: 8 page
Analytic Continuation for Asymptotically AdS 3D Gravity
We have previously proposed that asymptotically AdS 3D wormholes and black
holes can be analytically continued to the Euclidean signature. The analytic
continuation procedure was described for non-rotating spacetimes, for which a
plane t=0 of time symmetry exists. The resulting Euclidean manifolds turned out
to be handlebodies whose boundary is the Schottky double of the geometry of the
t=0 plane. In the present paper we generalize this analytic continuation map to
the case of rotating wormholes. The Euclidean manifolds we obtain are quotients
of the hyperbolic space by a certain quasi-Fuchsian group. The group is the
Fenchel-Nielsen deformation of the group of the non-rotating spacetime. The
angular velocity of an asymptotic region is shown to be related to the
Fenchel-Nielsen twist. This solves the problem of classification of rotating
black holes and wormholes in 2+1 dimensions: the spacetimes are parametrized by
the moduli of the boundary of the corresponding Euclidean spaces. We also
comment on the thermodynamics of the wormhole spacetimes.Comment: 28 pages, 14 figure
Finding the center reliably: robust patterns of developmental gene expression
We investigate a mechanism for the robust identification of the center of a
developing biological system. We assume the existence of two morphogen
gradients, an activator emanating from the anterior, and a co-repressor from
the posterior. The co-repressor inhibits the action of the activator in
switching on target genes. We apply this system to Drosophila embryos, where we
predict the existence of a hitherto undetected posterior co-repressor. Using
mathematical modelling, we show that a symmetric activator-co-repressor model
can quantitatively explain the precise mid-embryo expression boundary of the
hunchback gene, and the scaling of this pattern with embryo size.Comment: 4 pages, 3 figure
Seeing what you want to see: priors for one's own actions represent exaggerated expectations of success.
People perceive the consequences of their own actions differently to how they perceive other sensory events. A large body of psychology research has shown that people also consistently overrate their own performance relative to others, yet little is known about how these "illusions of superiority" are normally maintained. Here we examined the visual perception of the sensory consequences of self-generated and observed goal-directed actions. Across a series of visuomotor tasks, we found that the perception of the sensory consequences of one's own actions is more biased toward success relative to the perception of observed actions. Using Bayesian models, we show that this bias could be explained by priors that represent exaggerated predictions of success. The degree of exaggeration of priors was unaffected by learning, but was correlated with individual differences in trait optimism. In contrast, when observing these actions, priors represented more accurate predictions of the actual performance. The results suggest that the brain internally represents optimistic predictions for one's own actions. Such exaggerated predictions bind the sensory consequences of our own actions with our intended goal, explaining how it is that when acting we tend to see what we want to see.We thank J. D. Carlin for his help with acquiring eye gaze data. This work was funded by the Wellcome Trust [088324], Medical Research Council and a Scholar Award from the James S. McDonnell Foundation 21st Century Science Initiative: understanding human cognition (to James B. Rowe) as well as the Human Frontier Science Program and the Royal Society Noreen Murray Professorship in Neurobiology (to Daniel M. Wolpert); Noham Wolpe was funded by a Gates Cambridge Scholarship and the Raymond and Beverley Sackler Foundation.This is the final version of the article. It first appeared from Frontiers via http://dx.doi.org/10.3389/fnbeh.2014.0023
Learning, Social Intelligence and the Turing Test - why an "out-of-the-box" Turing Machine will not pass the Turing Test
The Turing Test (TT) checks for human intelligence, rather than any putative
general intelligence. It involves repeated interaction requiring learning in
the form of adaption to the human conversation partner. It is a macro-level
post-hoc test in contrast to the definition of a Turing Machine (TM), which is
a prior micro-level definition. This raises the question of whether learning is
just another computational process, i.e. can be implemented as a TM. Here we
argue that learning or adaption is fundamentally different from computation,
though it does involve processes that can be seen as computations. To
illustrate this difference we compare (a) designing a TM and (b) learning a TM,
defining them for the purpose of the argument. We show that there is a
well-defined sequence of problems which are not effectively designable but are
learnable, in the form of the bounded halting problem. Some characteristics of
human intelligence are reviewed including it's: interactive nature, learning
abilities, imitative tendencies, linguistic ability and context-dependency. A
story that explains some of these is the Social Intelligence Hypothesis. If
this is broadly correct, this points to the necessity of a considerable period
of acculturation (social learning in context) if an artificial intelligence is
to pass the TT. Whilst it is always possible to 'compile' the results of
learning into a TM, this would not be a designed TM and would not be able to
continually adapt (pass future TTs). We conclude three things, namely that: a
purely "designed" TM will never pass the TT; that there is no such thing as a
general intelligence since it necessary involves learning; and that
learning/adaption and computation should be clearly distinguished.Comment: 10 pages, invited talk at Turing Centenary Conference CiE 2012,
special session on "The Turing Test and Thinking Machines
Embryonic Pattern Scaling Achieved by Oppositely Directed Morphogen Gradients
Morphogens are proteins, often produced in a localised region, whose
concentrations spatially demarcate regions of differing gene expression in
developing embryos. The boundaries of expression must be set accurately and in
proportion to the size of the one-dimensional developing field; this cannot be
accomplished by a single gradient. Here, we show how a pair of morphogens
produced at opposite ends of a developing field can solve the pattern-scaling
problem. In the most promising scenario, the morphogens effectively interact
according to the annihilation reaction and the switch occurs
according to the absolute concentration of or . In this case embryonic
markers across the entire developing field scale approximately with system
size; this cannot be achieved with a pair of non-interacting gradients that
combinatorially regulate downstream genes. This scaling occurs in a window of
developing-field sizes centred at a few times the morphogen decay length.Comment: 24 pages; 11 figures; uses iopar
Independent Loop Invariants for 2+1 Gravity
We identify an explicit set of complete and independent Wilson loop
invariants for 2+1 gravity on a three-manifold , with
a compact oriented Riemann surface of arbitrary genus . In the
derivation we make use of a global cross section of the -principal
bundle over Teichm\"uller space given in terms of Fenchel-Nielsen coordinates.Comment: 11pp, 2 figures (postscript, compressed and uu-encoded), TeX,
Pennsylvania State University, CGPG-94/7-
Self-repair ability of evolved self-assembling systems in cellular automata
Self-repairing systems are those that are able to reconfigure themselves following disruptions to bring them back into a defined normal state. In this paper we explore the self-repair ability of some cellular automata-like systems, which differ from classical cellular automata by the introduction of a local diffusion process inspired by chemical signalling processes in biological development. The update rules in these systems are evolved using genetic programming to self-assemble towards a target pattern. In particular, we demonstrate that once the update rules have been evolved for self-assembly, many of those update rules also provide a self-repair ability without any additional evolutionary process aimed specifically at self-repair
An Exact No Free Lunch Theorem for Community Detection
A precondition for a No Free Lunch theorem is evaluation with a loss function
which does not assume a priori superiority of some outputs over others. A
previous result for community detection by Peel et al. (2017) relies on a
mismatch between the loss function and the problem domain. The loss function
computes an expectation over only a subset of the universe of possible outputs;
thus, it is only asymptotically appropriate with respect to the problem size.
By using the correct random model for the problem domain, we provide a
stronger, exact No Free Lunch theorem for community detection. The claim
generalizes to other set-partitioning tasks including core/periphery
separation, -clustering, and graph partitioning. Finally, we review the
literature of proposed evaluation functions and identify functions which
(perhaps with slight modifications) are compatible with an exact No Free Lunch
theorem
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