2,048 research outputs found
Dynamics of Internal Models in Game Players
A new approach for the study of social games and communications is proposed.
Games are simulated between cognitive players who build the opponent's internal
model and decide their next strategy from predictions based on the model. In
this paper, internal models are constructed by the recurrent neural network
(RNN), and the iterated prisoner's dilemma game is performed. The RNN allows us
to express the internal model in a geometrical shape. The complicated
transients of actions are observed before the stable mutually defecting
equilibrium is reached. During the transients, the model shape also becomes
complicated and often experiences chaotic changes. These new chaotic dynamics
of internal models reflect the dynamical and high-dimensional rugged landscape
of the internal model space.Comment: 19 pages, 6 figure
Universal neural field computation
Turing machines and G\"odel numbers are important pillars of the theory of
computation. Thus, any computational architecture needs to show how it could
relate to Turing machines and how stable implementations of Turing computation
are possible. In this chapter, we implement universal Turing computation in a
neural field environment. To this end, we employ the canonical symbologram
representation of a Turing machine obtained from a G\"odel encoding of its
symbolic repertoire and generalized shifts. The resulting nonlinear dynamical
automaton (NDA) is a piecewise affine-linear map acting on the unit square that
is partitioned into rectangular domains. Instead of looking at point dynamics
in phase space, we then consider functional dynamics of probability
distributions functions (p.d.f.s) over phase space. This is generally described
by a Frobenius-Perron integral transformation that can be regarded as a neural
field equation over the unit square as feature space of a dynamic field theory
(DFT). Solving the Frobenius-Perron equation yields that uniform p.d.f.s with
rectangular support are mapped onto uniform p.d.f.s with rectangular support,
again. We call the resulting representation \emph{dynamic field automaton}.Comment: 21 pages; 6 figures. arXiv admin note: text overlap with
arXiv:1204.546
The Evolution of Reaction-diffusion Controllers for Minimally Cognitive Agents
No description supplie
Diversity, Stability, Recursivity, and Rule Generation in Biological System: Intra-inter Dynamics Approach
Basic problems for the construction of a scenario for the Life are discussed.
To study the problems in terms of dynamical systems theory, a scheme of
intra-inter dynamics is presented. It consists of internal dynamics of a unit,
interaction among the units, and the dynamics to change the dynamics itself,
for example by replication (and death) of units according to their internal
states. Applying the dynamics to cell differentiation, isologous
diversification theory is proposed. According to it, orbital instability leads
to diversified cell behaviors first. At the next stage, several cell types are
formed, first triggered by clustering of oscillations, and then as attracting
states of internal dynamics stabilized by the cell-to-cell interaction. At the
third stage, the differentiation is determined as a recursive state by cell
division. At the last stage, hierarchical differentiation proceeds, with the
emergence of stochastic rule for the differentiation to sub-groups, where
regulation of the probability for the differentiation provides the diversity
and stability of cell society. Relevance of the theory to cell biology is
discussed.Comment: 19 pages, Int.J. Mod. Phes. B (in press
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