1,203 research outputs found
Categorical Aspects of Parameter Learning
Parameter learning is the technique for obtaining the probabilistic
parameters in conditional probability tables in Bayesian networks from tables
with (observed) data --- where it is assumed that the underlying graphical
structure is known. There are basically two ways of doing so, referred to as
maximal likelihood estimation (MLE) and as Bayesian learning. This paper
provides a categorical analysis of these two techniques and describes them in
terms of basic properties of the multiset monad M, the distribution monad D and
the Giry monad G. In essence, learning is about the reltionships between
multisets (used for counting) on the one hand and probability distributions on
the other. These relationsips will be described as suitable natural
transformations
Strategic Port Graph Rewriting: An Interactive Modelling and Analysis Framework
We present strategic portgraph rewriting as a basis for the implementation of
visual modelling and analysis tools. The goal is to facilitate the
specification, analysis and simulation of complex systems, using port graphs. A
system is represented by an initial graph and a collection of graph rewriting
rules, together with a user-defined strategy to control the application of
rules. The strategy language includes constructs to deal with graph traversal
and management of rewriting positions in the graph. We give a small-step
operational semantics for the language, and describe its implementation in the
graph transformation and visualisation tool PORGY.Comment: In Proceedings GRAPHITE 2014, arXiv:1407.767
Markovian Testing Equivalence and Exponentially Timed Internal Actions
In the theory of testing for Markovian processes developed so far,
exponentially timed internal actions are not admitted within processes. When
present, these actions cannot be abstracted away, because their execution takes
a nonzero amount of time and hence can be observed. On the other hand, they
must be carefully taken into account, in order not to equate processes that are
distinguishable from a timing viewpoint. In this paper, we recast the
definition of Markovian testing equivalence in the framework of a Markovian
process calculus including exponentially timed internal actions. Then, we show
that the resulting behavioral equivalence is a congruence, has a sound and
complete axiomatization, has a modal logic characterization, and can be decided
in polynomial time
Model Checking Based Test Generation from P Systems Using P-Lingua
This paper presents an approach for P system testing, that uses model-
checking for automatic test generation and P-Lingua as specification language. This
approach is based on a transformation of the transitional, non-deterministic, cell-like
P system into a Kripke structure, which is further used for test generation, by adding
convenient temporal logic specifications. This paper extends our previous work in this
field to multi-membrane, transitional P system, having cooperative rules, communication between membranes and membrane dissolution. A tool, which takes as input a P
system specified in P-Lingua and translates it into the language accepted by the model
checker NuSMV was developed and used for test case generation. Some hints regarding
the automatic test generation using NuSMV and P-Lingua are also given
Fast Hardware Implementations of Static P Systems
In this article we present a simulator of non-deterministic static P systems
using Field Programmable Gate Array (FPGA) technology. Its major feature
is a high performance, achieving a constant processing time for each transition. Our
approach is based on representing all possible applications as words of some regular
context-free language. Then, using formal power series it is possible to obtain the
number of possibilities and select one of them following a uniform distribution, in
a fair and non-deterministic way. According to these ideas, we yield an implementation
whose results show an important speed-up, with a strong independence from
the size of the P system.Ministry of Science and Innovation of the Spanish Government under the project TEC2011-27936 (HIPERSYS)European Regional Development Fund (ERDF)Ministry of Education of Spain (FPU grant AP2009-3625)ANR project SynBioTI
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