Service composition in stochastic settings

With the growth of the Internet-of-Things and online Web services, more services with more capabilities are available to us. The ability to generate new, more useful services from existing ones has been the focus of much research for over a decade. The goal is, given a specification of the behavior of the target service, to build a controller, known as an orchestrator, that uses existing services to satisfy the requirements of the target service. The model of services and requirements used in most work is that of a finite state machine. This implies that the specification can either be satisfied or not, with no middle ground. This is a major drawback, since often an exact solution cannot be obtained. In this paper we study a simple stochastic model for service composition: we annotate the tar- get service with probabilities describing the likelihood of requesting each action in a state, and rewards for being able to execute actions. We show how to solve the resulting problem by solving a certain Markov Decision Process (MDP) derived from the service and requirement specifications. The solution to this MDP induces an orchestrator that coincides with the exact solution if a composition exists. Otherwise it provides an approximate solution that maximizes the expected sum of values of user requests that can be serviced. The model studied although simple shades light on composition in stochastic settings and indeed we discuss several possible extensions

Chiral transition and deconfinement in N_f = 2 QCD

The transition is studied by means of a disorder parameter detecting condensation of magnetic monopoles in the vacuum. The deconfining transition is found to coincide with the chiral transition and the susceptibility \rho, related to the disorder parameter, is consistent with a first order phase transition.Comment: 3 pages, 2 figures. Poster presented at Lattice2004(topology), Fermilab, June 21-26, 200

Beyond divide and rule: weak dictators, natural resources and civil conflict

We propose a model where an autocrat rules over an ethnically divided society. The dictator selects the tax rate over domestic production and the nation's natural resources to maximize his rents under the threat of a regime-switching revolution. We show that a weak ruler may let the country plunge in civil war to increase his personal rents. Inter-group fighting weakens potential opposition to the ruler, thereby allowing him to increase fiscal pressure. We show that the presence of natural resources exacerbatesthe incentives of the ruler to promote civil conflict for his own profit, especially if the resources are unequally distributed across ethnic groups. We validate the main predictions of the model using cross-country data over the period 1960-2007, and show that our empirical results are not likely to be driven by omitted observable determinants of civil war incidence or by unobservable country-specific heterogeneity.

Color confinement and dual superconductivity of the vacuum. III

It is demonstrated that monopole condensation in the confined phase of SU(2) and SU(3) gauge theories is independent of the specific Abelian projection used to define the monopoles. Hence the dual excitations which condense in the vacuum to produce confinement must have magnetic U(1) charge in all the Abelian projections. Some physical implications of this result are discussed.Comment: 6 pages, 5 postscript figure

Extending DL-LiteR TBoxes with view definitions

Views are a mechanisms for precomputing answers to query of particular significance. Views have a definition (the query itself) and an extension obtained by evaluating the query over the data sources. Views are used for controlling the access to data and keep data even when the original sources are not accessible anymore. In this paper we introduce views definitions in DL-LiteR ontologies as an additional form of assertions in the TBox, and we study the basic reasoning tasks involving them, including consistency, containment, disjointness, projection classification, and query answering

LTLf best-effort synthesis in nondeterministic planning domains

We study best-effort strategies (aka plans) in fully observable nondeterministic domains (FOND) for goals expressed in Linear Temporal Logic on Finite Traces (LTLf). The notion of best-effort strategy has been introduced to also deal with the scenario when no agent strategy exists that fulfills the goal against every possible nondeterministic environment reaction. Such strategies fulfill the goal if possible, and do their best to do so otherwise. We present a game-theoretic technique for synthesizing best-effort strategies that exploit the specificity of nondeterministic planning domains. We formally show its correctness and demonstrate its effectiveness experimentally, exhibiting a much greater scalability with respect to a direct best-effort synthesis approach based on re-expressing the planning domain as generic environment specifications

Markov abstractions for PAC reinforcement learning in non-Markov decision processes

Our work aims at developing reinforcement learning algorithms that do not rely on the Markov assumption. We consider the class of Non-Markov Decision Processes where histories can be abstracted into a finite set of states while preserving the dynamics. We call it a Markov abstraction since it induces a Markov Decision Process over a set of states that encode the non-Markov dynamics. This phenomenon underlies the recently introduced Regular Decision Processes (as well as POMDPs where only a finite number of belief states is reachable). In all such kinds of decision process, an agent that uses a Markov abstraction can rely on the Markov property to achieve optimal behaviour. We show that Markov abstractions can be learned during reinforcement learning. Our approach combines automata learning and classic reinforcement learning. For these two tasks, standard algorithms can be employed. We show that our approach has PAC guarantees when the employed algorithms have PAC guarantees, and we also provide an experimental evaluation

Mimicking Behaviors in Separated Domains

Devising a strategy to make a system mimic behaviors from another system is a problem that naturally arises in many areas of Computer Science. In this work, we interpret this problem in the context of intelligent agents, from the perspective of LTLf , a formalism commonly used in AI for expressing finite-trace properties. Our model consists of two separated dynamic domains, DA and DB , and an LTLf specification that formalizes the notion of mimicking by mapping properties on behaviors (traces) of DA into properties on behaviors of DB . The goal is to synthesize a strategy that step-by-step maps every behavior of DA into a behavior of DB so that the specification is met. We consider several forms of mapping specifications, ranging from simple ones to full LTLf , and for each, we study synthesis algorithms and computational properties

From Component-Based Architectures to Microservices: A 25-years-long Journey in Designing and Realizing Service-Based Systems

Distributed information systems and applications are generally described in terms of components and interfaces among them. How these component-based architectures have been designed and implemented evolved over the years, giving rise to the so-called paradigm of Service-Oriented Computing (SOC). In this chapter, we will follow a 25-years-long journey on how design methodologies and supporting technologies influenced one each other, and we discuss how already back in the late 90s the ancestors of the SOC paradigm were there, already paving the way for the technological evolution recently leading to microservice architectures and serverless computing

A finite temperature investigation of dual superconductivity in the modified SO(3) lattice gauge theory

We study the SO(3) lattice gauge theory in 3+1 dimensions with the adjoint Wilson action modified by a $\mathbb{Z}_2$ monopole suppression term and by means of the Pisa disorder operator. We find evidence for a finite temperature deconfinement transition driven by the condensation of U(1) magnetic charges. A finite-size scaling test shows consistency with the critical exponents of the 3D Ising model.Comment: 14 pages, 4 figures. Layout changed, figures, text and references added. To appear on Physics Letters