16,611 research outputs found
The Role of Noise in the Spatial Public Goods Game
In this work we aim to analyze the role of noise in the spatial Public Goods
Game, one of the most famous games in Evolutionary Game Theory. The dynamics of
this game is affected by a number of parameters and processes, namely the
topology of interactions among the agents, the synergy factor, and the strategy
revision phase. The latter is a process that allows agents to change their
strategy. Notably, rational agents tend to imitate richer neighbors, in order
to increase the probability to maximize their payoff. By implementing a
stochastic revision process, it is possible to control the level of noise in
the system, so that even irrational updates may occur. In particular, in this
work we study the effect of noise on the macroscopic behavior of a finite
structured population playing the Public Goods Game. We consider both the case
of a homogeneous population, where the noise in the system is controlled by
tuning a parameter representing the level of stochasticity in the strategy
revision phase, and a heterogeneous population composed of a variable
proportion of rational and irrational agents. In both cases numerical
investigations show that the Public Goods Game has a very rich behavior which
strongly depends on the amount of noise in the system and on the value of the
synergy factor. To conclude, our study sheds a new light on the relations
between the microscopic dynamics of the Public Goods Game and its macroscopic
behavior, strengthening the link between the field of Evolutionary Game Theory
and statistical physics.Comment: 14 pages, 3 figure
Patterning the insect eye: from stochastic to deterministic mechanisms
While most processes in biology are highly deterministic, stochastic
mechanisms are sometimes used to increase cellular diversity, such as in the
specification of sensory receptors. In the human and Drosophila eye,
photoreceptors sensitive to various wavelengths of light are distributed
randomly across the retina. Mechanisms that underlie stochastic cell fate
specification have been analysed in detail in the Drosophila retina. In
contrast, the retinas of another group of dipteran flies exhibit highly ordered
patterns. Species in the Dolichopodidae, the "long-legged" flies, have regular
alternating columns of two types of ommatidia (unit eyes), each producing
corneal lenses of different colours. Individual flies sometimes exhibit
perturbations of this orderly pattern, with "mistakes" producing changes in
pattern that can propagate across the entire eye, suggesting that the
underlying developmental mechanisms follow local, cellular-automaton-like
rules. We hypothesize that the regulatory circuitry patterning the eye is
largely conserved among flies such that the difference between the Drosophila
and Dolichopodidae eyes should be explicable in terms of relative interaction
strengths, rather than requiring a rewiring of the regulatory network. We
present a simple stochastic model which, among its other predictions, is
capable of explaining both the random Drosophila eye and the ordered, striped
pattern of Dolichopodidae.Comment: 24 pages, 4 figure
GENETIC ALGORITHM FOR BINARY AND FUNCTIONAL DECISION DIAGRAMS OPTIMIZATION
Decision diagrams (DD) are a widely used data structure for discrete functions representation. The major problem in DD-based applicationsis the DD size minimization (reduction of the number of nodes), because their size is dependent on the variables order. Genetic algorithms are often used in different optimization problems including the DD size optimization. In this paper, we apply the genetic algorithm to minimize the size of both Binary Decision Diagrams (BDDs) and Functional Decision Diagrams (FDDs). In both cases, in the proposed algorithm, a Bottom-Up Partially Matched Crossover (BU-PMX) is used as the crossover operator. In the case of BDDs, mutation is done in the standard way by variables exchanging. In the case of FDDs, the mutation by changing the polarity of variables is additionally used. Experimental results of optimization of the BDDs and FDDs of the set of benchmark functions are also presented
Neuron as a reward-modulated combinatorial switch and a model of learning behavior
This paper proposes a neuronal circuitry layout and synaptic plasticity
principles that allow the (pyramidal) neuron to act as a "combinatorial
switch". Namely, the neuron learns to be more prone to generate spikes given
those combinations of firing input neurons for which a previous spiking of the
neuron had been followed by a positive global reward signal. The reward signal
may be mediated by certain modulatory hormones or neurotransmitters, e.g., the
dopamine. More generally, a trial-and-error learning paradigm is suggested in
which a global reward signal triggers long-term enhancement or weakening of a
neuron's spiking response to the preceding neuronal input firing pattern. Thus,
rewards provide a feedback pathway that informs neurons whether their spiking
was beneficial or detrimental for a particular input combination. The neuron's
ability to discern specific combinations of firing input neurons is achieved
through a random or predetermined spatial distribution of input synapses on
dendrites that creates synaptic clusters that represent various permutations of
input neurons. The corresponding dendritic segments, or the enclosed individual
spines, are capable of being particularly excited, due to local sigmoidal
thresholding involving voltage-gated channel conductances, if the segment's
excitatory and absence of inhibitory inputs are temporally coincident. Such
nonlinear excitation corresponds to a particular firing combination of input
neurons, and it is posited that the excitation strength encodes the
combinatorial memory and is regulated by long-term plasticity mechanisms. It is
also suggested that the spine calcium influx that may result from the
spatiotemporal synaptic input coincidence may cause the spine head actin
filaments to undergo mechanical (muscle-like) contraction, with the ensuing
cytoskeletal deformation transmitted to the axon initial segment where it
may...Comment: Version 5: added computer code in the ancillary files sectio
Single and Composite Hot Subdwarf Stars in the Light of 2MASS Photometry
Utilizing the Two Micron All Sky Survey (2MASS) Second Incremental Data
Release Catalog, we have retrieved near-IR magnitudes for several hundred hot
subdwarfs (sdO and sdB stars) drawn from the "Catalogue of Spectroscopically
Identified Hot Subdwarfs" (Kilkenny, Heber, & Drilling 1988, 1992). This sample
size greatly exceeds that of previous studies of hot subdwarfs. Examining 2MASS
photometry alone or in combination with visual photometry (Johnson BV or
Stromgren uvby) available in the literature, we show that it is possible to
identify hot subdwarf stars that exhibit atypically red IR colors that can be
attributed to the presence of an unresolved late type companion. Utilizing this
large sample, we attempt for the first time to define an approximately volume
limited sample of hot subdwarfs. We discuss the considerations, biases, and
difficulties in defining such a sample.
We find that, of the hot subdwarfs in Kilkenny et al., about 40% in a
magnitude limited sample have colors that are consistent with the presence of
an unresolved late type companion. Binary stars are over-represented in a
magnitude limited sample. In an approximately volume limited sample the
fraction of composite-color binaries is about 30%.Comment: to appear in Sept 2003 AJ, 41 pages total, 12 figures, 2 tables are
truncated (full tables to appear in electronic journal or available by
request
- …