A Markovian Extension of Valiant′s Learning Model

A Markovian Extension of Valiant's Learning Model (Extended Abstract)

Formalizing the process of natural induction and justifying its predictive value is not only basic to the philosophy of science, but is also an essential ingredient of any formal theory of learning. A formulation of the process of induction which is intuitively compelling and reasonable from a computational point of view is arrived a t by equating the process of induction with Occam Algorithms ...

sPBC : A Markovian Extension of nite PBC ?

investigating the feasibility of a proposed model for geometric design of deployable arch structures

deployable scissor type structures are composed of the so-called scissor-like elements (sles), which are connected to each other at an intermediate point through a pivotal connection and allow them to be folded into a compact bundle for storage or transport. several sles are connected to each other in order to form units with regular polygonal plan views. the sides and radii of the polygons are...

MarCaSPiS: a Markovian Extension of a Calculus for Services

Service Oriented Computing (SOC) is a design paradigm that has evolved from earlier paradigms including object-orientation and component-based software engineering. Important features of services are compositionality, context-independence, encapsulation and re-usability. To support the formal design and analysis of SOC applications recently a number of Service Oriented Calculi have been propose...

sPBC: A Markovian Extension of Finite Petri box calculus

In this paper we present a stochastic extension of finite PBC, sPBC, in which actions have a stochastic delay associated, which is taken from a negative exponential distribution. We define for the language both an operational and a denotational semantics, using a class of labelled stochastic Petri net as supporting values. In this paper we restrict our attention to finite sPBC, i.e., we conside...