Pablo López

Monadic concurrent linear logic programming

Lolli is a logic programming language based on the asynchronous propositions of intuitionistic linear logic. It uses a backward chaining, backtracking operational semantics. In this paper we extend Lolli with the remaining connectives of intuitionistic linear logic restricted to occur inside a monad, an idea taken from the concurrent logical framework (CLF). The resulting language, called LolliMon, has a natural forward chaining, committed choice operational semantics inside the monad, while retaining Lollis semantics outside the monad. LolliMon thereby cleanly integrates both concurrency and saturation with logic programming search. We illustrate its expressive power through several examples including an implementation of the pi-calculus, a call-by-need lambda-calculus, and several saturating algorithms presented in logical form.

A Service-Oriented Model for Embedded Peer-to-Peer Systems

This paper introduces a service-oriented model for the development of Peer-to-Peer (P2P) systems. We first describe the set of abstract primitives supported by the model, and then the semantics for a simple calculus over these primitives that provides a solid ground to develop tools for the analysis and verification of P2P specifications.

A Tag-Frame System of Resource Management for Proof Search in Linear-Logic Programming

In programming languages based on linear logic, the program can grow and shrink in a nearly arbitrary manner over the course of execution. Since the introduction of the I/O model of proof search [11, 12], a number of refinements have been proposed with the intention of reducing its degree of non-determinism [3, 4, 12, 13, 14]. Unfortunately each of these systems has had some limitations. In particular, while the resource management systems of Cervesato et al. [3, 4] and the frame system of Lopez and Pimentel [14] obtained the greatest degree of determinism, they required global operations on the set of clauses which were suitable only for interpreter-based implementations. In contrast the level-tags system of Hodas, et al. relied only on relabeling tags attached to individual formulas, and was hence appropriate as the specification of an abstract machine. However it retained more non-determinism than the resource management systems. This led to a divergence in the operational semantics of the interpreted and compiled versions of the language Lolli. In this paper we propose a tag-frame system which recaptures the behavior of the resource management systems, while being appropriate as a foundation of a compiled implementation.

Resource Management in Linear Logic Proof Search Revisited

Linear logic provides a logical framework to express fundamental computational concepts in a declarative style. As a consequence, it has been used as a sound foundation for the design of expressive programming and specification languages. Unfortunately, linearity is as convenient for specifying as difficult to implement. In particular, the successful implementation of linear logic languages and provers involving context splitting strongly depends on the efficiency of the method computing a suitable split. A number of solutions have been proposed, referred to as lazy splitting or resource management systems. In this paper, we present a new resource management system for the Lolli linear logic language. We show that the choice of the structure employed to represent the contexts has a strong influence on the overall performcince of the resource management system. We also estimate the performance of previous proposals, and compare them to our new system.

Implementing efficient resource management for linear logic programming

The Tag-Frame system of resource management [1] reunited two divergent threads of linear logic programming research by achieving the efficient proof search behaviour of abstract systems, such as [2], while using a low-level tag-based approach, as in [3], suitable for specifying an abstract machine. However, Tag-Frame relies on set operations which are linear in the size of the sets, and is not as efficient, in general, as it could be. We present a new tag-based derivation system which relies solely on low-level concepts to implement efficient resource management, where most linear time operations have been replaced by constant time ones. Though motivated and informed by the Tag-Frame system, we derive our system directly from, and prove its correctness with respect to the system of Cervesato et al. [2]. An abstract machine based on the new system has been implemented by Tamura and Banbara, and its performance compared to their previous machine.

A formalization of the SMEPP model in Maude

This paper introduces a service-oriented model for the description of embedded Peer-to-Peer (EP2P) systems and formalizes the proposed model in Maude. The model is organized around the notions of groups of peers and services offered by these groups. We first summarize the main concepts of the model and then present αSMoL, an abstract language with a formal semantics that provides a solid ground to develop tools for the automated analysis and verification of EP2P specifications. We then describe a formalization of αSMoL in Maude, and introduce an example to illustrate both the expressive power of the model and the possibilities of Maude to support automated verification of properties of αSMoL programs.

Towards a Model of Volume Transmission in Biological and Artificial Neural Networks: A CAST Approach

At present, a new type of process for signalling between cells seems to be emerging, the diffusion or volume transmission. The volume transmission is performed by means of a gas diffusion process, which is obtained with a diffusive type of signal (NO). We present in this paper a CAST approach, in order to develop a NOdi ffusion model, away from a biologically plausible morphology, that provides a formal framework for the establishing of neural signalling capacity of NOin biological and artificial neural environments. It is also presented a study which shows implications of volume transmission in the emergence of complex structures and self-organisation processes in both biological and artificial neural netwoks. Finally, we present the diffusion version of the Associative Network (AN) [6], the Diffusion Associative Network (DAN), where a more general framework of neural learning, which is based in synaptic and volume transmission, is considered.

Self-Organizing Maps for Early Detection of Denial of Service Attacks

Detection and early alert of Denial of Service (DoS) attacks are very important actions to make appropriate decisions in order to minimize their negative impact. DoS attacks have been catalogued as of high-catastrophic index and hard to defend against. Our study presents advances in the area of computer security against DoS attacks. In this chapter, a flexible method is presented, capable of effectively tackling and overcoming the challenge of DoS (and distributed DoS) attacks using a CISDAD (Computer Intelligent System for DoS Attacks Detection). It is a hybrid intelligent system with a modular structure: a pre-processing module (non neural) and a processing module based on Kohonen Self-Organizing artificial neural networks. The proposed system introduces an automatic differential detection of several Normal Traffic and several Toxic Traffics, clustering them upon its Transport-Layer-Protocol behavior. Two computational studies of CISDAD working with real networking traffic will be described, showing a high level of effectiveness in the CISDAD detection process. Finally, in this chapter, the possibility for specific adaptation to the Healthcare environment that CISDAD can offer is introduced.

Isolating Resource Consumption in Linear Logic Proof Search (extended abstract)

This work presents an extension of the Tag-Frame resource management system previously developed by the authors. The extended proof system is able to isolate the consumption of a given goal/clause without incurring significant extra runtime costs. We believe this feature may have a number of applications, in particular for debugging linear logic programs and specifications in a proof-theoretic setting. This point is illustrated by means of a simple example.

Nitric Oxide Diffusion and Multi-compartmental Systems: Modeling and Implications

The volume transmission (VT), a new type of cellular signaling, is based on the diffusion of neuro-active substances such as Nitric Oxide (NO) in the Extracellular Space (ECS). It is not homogeneous, critically dependent on, and limited by, its structure and physico-chemical properties. We present a different computational model of the NO diffusion based on multi-compartmental systems and transportation phenomena. It allows incorporating these ECS characteristics and the biological features and restrictions of the NO dynamics.