Logic Programming

Misyurov D.A. Dialectical formulas based on the binary notation as the development formulas // Credo New. 2012. №2

by Dmitry Misyurov

The article suggests dialectical formulas based on the binary notation as the development formulas: formula with... more The article suggests dialectical formulas based on the binary notation as the development formulas: formula with dominant and the non-dominant elements; universal formula; formula with symbolic weight of elements; tautological formula. For example, it suggests an opportunity to use the dialectical formulas for modeling and artificial intelligence creation, etc.

Foundations of the rule-based system ρLog

by Temur Kutsia

Moral Reasoning Under Uncertainty

by The Anh Han

co-authored with A. Saptawijaya and L. M. Pereira.
In Proceedings of the 18th International Conference on Logic for Programming Artificial Intelligence and Reasoning (LPAR 2012), Springer LNAI, 2012

We present a Logic Programming framework for moral reasoning under uncertainty. It is enacted by a coherent... more We present a Logic Programming framework for moral reasoning under uncertainty. It is enacted by a coherent combination of our two previously implemented systems, Evolution Prospection for decision making, and P-log for probabilistic inference. It allows computing available moral judgments via distinct kinds of prior and post preferences. In introducing various aspects of uncertainty into cases of classical trolley problem moral dilemmas, we show how they may appropriately influence moral judgments, allowing decision makers to opt for different choices, and for these to be externally appraised, even when subject to incomplete evidence, as in courts.

Identifying Refactoring Opportunities Using Logic Meta Programming

by Tom Mens

Published at CSMR 2003, co-authored by Tom Tourwé

In this paper, we show how automated support can be provided for identifying refactoring opportunities, e.g., when an... more In this paper, we show how automated support can be provided for identifying refactoring opportunities, e.g., when an application’s design should be refactored and which refactoring(s) in particular should be applied. Such support is achieved by using the technique of logic meta programming to detect socalled bad smells and by defining a framework that uses this information to propose adequate refactorings. We report on some initial but promising experiments that were applied using the proposed techniques.

Maintaining software through intentional source-code views

by Tom Mens

Authors: Kim Mens, Tom Mens, Michel Wermelinger. Proceedings of ACM Software Engineering and Knowledge Engineering Conference (SEKE 2002).
(c) ACM 2002

Maintaining the source code of large software systems is hard. One underlying cause is that existing modularisation... more Maintaining the source code of large software systems is hard. One underlying cause is that existing modularisation mechanisms are inadequate to handle crosscutting concerns. We propose intentional source-code views as an intuitive and lightweight means of modelling such concerns. They increase our ability to understand, modularise and browse the source code by grouping together source-code entities that address the same concern. They facilitate software development and evolution, because alternative descriptions of the same intentional view can be checked for consistency and relations among intentional views can be defined and verified. Finally, they enable us to specify knowledge developers have about source code that is not captured by traditional program documentation mechanisms.
Our intentional view model is implemented in a logic metaprogramming language that can reason about and manipulate object-oriented source code directly. The proposed model has been validated on the evolution of a medium-sized object-oriented application in Smalltalk, and a prototype tool has been implemented.

Evolution Prospection with Intention Recognition via Computational Logic

by The Anh Han

Master Thesis - Technical University of  Dresden, Germany and Universidade Nova de Lisbon, Portugal, 2009

This thesis concerns the problem of modelling evolving prospective agent systems. Inasmuch a prospective agent looks... more This thesis concerns the problem of modelling evolving prospective agent systems. Inasmuch a prospective agent looks ahead a number of steps into the future, it is confronted with the problem of having several different possible courses of evolution, and therefore needs to be able to prefer amongst them to determine the best to follow as seen from its present state. Based on historical information as well as quantitative and qualitative a posteriori evaluation of its possible evolutions, the agent is equipped with so- called evolution-level preferences mechanism. In addition, to enable such a prospective agent to evolve, we provide a way for modelling its evolving knowledge base, including environment triggering of active goals, context- sensitive preferences and integrity constraints. Furthermore, to allow an evolving prospective agent acting under uncertainty, P-log is employed for representing probabilistic knowledge. Finally, such agents are enhanced with an ability of intention recognition, via combination of Causal Bayes Net- works and plan attribution.
Besides, several examples are exhibited to illustrate the proffered con- cepts and features. We also show how the evolving prospective agent system can be applied to model morality and provide supports for elderly people.

Programación lógica

by Miguel Angel Alonso Pardo

Tórculo Edicións, Santiago de Compostela, Spain, 1994. ISBN 84-88967-36-5 (200 pp).

Intention Recognition with Evolution Prospection and Causal Bayes Networks

by The Anh Han

co-authored with LM Pereira, Computational Intelligence for Engineering Systems Intelligent Systems, Control and Automation: Science and Engineering, 2011, Volume 46, 1-33

We describe a novel approach to tackle intention recognition, by combining dynamically configurable and... more We describe a novel approach to tackle intention recognition, by combining dynamically configurable and situation-sensitive Causal Bayes Networks plus plan generation techniques. Given some situation, such networks enable the recognizing agent to come up with the most likely intentions of the intending agent, i.e. solve one main issue of intention recognition. And, in case of having to make a quick decision, focus on the most important ones. Furthermore, the combination with plan generation provides a significant method to guide the recognition process with respect to hidden actions and unobservable effects, in order to confirm or disconfirm likely intentions. The absence of this articulation is a main drawback of the approaches using Bayes Networks solely, due to the combinatorial problem they encounter. We explore and exemplify its application, in the Elder Care context, of the ability to perform Intention Recognition and of wielding Evolution Prospection methods to help the Elder achieve its intentions. This is achieved by means of an articulate use of a Causal Bayes Network to heuristically gauge probable general intention #x2013; combined with specific generation of plans involving preferences – for checking which such intentions are plausibly being carried out in the specific situation at hand, and suggesting actions to the Elder. The overall approach is formulated within one coherent and general logic programming framework and implemented system. The paper recaps required background and illustrates the approach via an extended application example.

Evolution prospection in decision making

by The Anh Han

co-authored with LM Pereira, Journal of Intelligent Decision Making, 2009

This work concerns the problem of modelling evolving prospective agent systems. Inasmuch a prospective agent [1] looks... more This work concerns the problem of modelling evolving prospective agent systems. Inasmuch a prospective agent [1] looks ahead a number of steps into the future, it is confronted with the problem of having several different possible courses of evolution, and therefore needs to be able to prefer amongst them to decide the best to follow as seen from its present state. First it needs a priori preferences for the generation of likely courses of evolution. Subsequently, this being one main contribution of this paper, based on the historical information as well as on a mixture of quantitative and qualitative a posteriori evaluation of its possible evolutions, we equip our agent with so-called evolution-level preferences mechanism, involving three distinct types of commitment. In addition, one other main contribution, to enable such a prospective agent to evolve, we provide a way for modelling its evolving knowledge base, including environment and course of evolution triggering of all active goals (desires), context-sensitive preferences and integrity constraints. We exhibit several examples to illustrate the proposed concepts.

An implementation of extended P-log using XASP

by The Anh Han

ICLP 2008

We propose a new approach for implementing P-log using XASP, the interface of XSB with Smodels. By using the tabling... more We propose a new approach for implementing P-log using XASP, the interface of XSB with Smodels. By using the tabling mechanism of XSB, our system is most of the times faster than P-log. In addition, our implementation has query features not supported by P-log, as well as new set operations for domain definition.

Some questions about non-termination in DCGs

by Miguel Angel Alonso Pardo

in Maria Chiara Meo and Manuel Vilares Ferro (eds.), APPIA-GULP-PRODE'99 Joint Conference on Declarative Programming, Proceedings, pp. 545-558, L'Aquila, Italy, 1999.

Programación lógica (segunda edición)

by Miguel Angel Alonso Pardo

Tórculo Edicións, Santiago de Compostela, Spain, 1996. ISBN 84-89641-18-8 (252 pp).

Object-Oriented Computations In Logic Programming

by Andrea Omicini

Semi-Stable Semantics

by Martin Caminada

Martin Caminada, Walter Carnielli and Paul Dunne
Journal of Logic and Computation (in print)

In this paper, we examine an argument-based semantics called semi-stable semantics. Semi-stable semantics is quite... more In this paper, we examine an argument-based semantics called semi-stable semantics. Semi-stable semantics is quite close to traditional stable semantics in the sense that every stable extension is also a semi-stable extension. One of the advantages of semi-stable semantics is that for finite argumentation frameworks there always exists at least one semi-stable extension. Furthermore, if there also exists at least one stable extension, then the semi-stable extensions coincide with the stable extensions. Semi-stable semantics can be seen as a general approach that can be applied to abstract argumentation, as well as to fields like default logic and answer set programming, yielding an interpretation with properties very similar to those of paraconsistent logic, including the properties of crash resistance and backward compatibility.

Towards Shrink-Wrapped Security: Practically Incorporating Context Into Security Services

by Paulo Shakarian

Gleneesha Johnson, Paulo Shakarian, Neha Gupta, Ashok Agrawala,
Intl. Symposium on Frontiers in Ambient and Mobile Systems
(FAMS-2011); accepted, 2011

The mobile workforce is rapidly increasing, and technological advances make it feasible for these workers to have... more The mobile workforce is rapidly increasing, and technological advances make it feasible for these workers to have ubiquitous access to a variety of resources with various protection requirements. The dynamic computing environment of these workers mandates a security paradigm in which security is tightly coupled with a user's current situation. We have proposed a security paradigm to achieve this, called Shrink-Wrapped Security, in which security is constantly adapting to a user's current situation, and a comprehensive amount of security-relevant context is used to characterize a user's situation. We present an approach that uses generalized annotated programs (GAPs) to practically incorporate such context into security services, with a focus on access control. This allows us to represent context in a principled manner; consistently make security-related decisions; easily make temporary, ad-hoc changes to a security policy; and give a user feedback when access is denied so that she can make the appropriate adjustments.

From Programs to Object Code Using Logic and Logic Programming

by Jonathan Bowen

From Programs to Object Code and Back Again Using Logic Programming: Compilation and Decompilation

by Jonathan Bowen

Possibilistic semantics for logic programs with ordered disjunction

by Roberto Confalonieri

A scalable framework for modeling competitive diffusion in social networks

by Paulo Shakarian

Matthias Broecheler, Paulo Shakarian, V.S. Subrahmanian, IEEE SocialCom 2010 (symposium section); August 2010

Multiple phenomena often diffuse through a social
network, sometimes in competition with one another. Product... more Multiple phenomena often diffuse through a social
network, sometimes in competition with one another. Product
adoption and political elections are two examples where network
diffusion is inherently competitive in nature. For example, individuals
may choose to only select one product from a set of
competing products (i.e. most people will need only one cell-phone
provider) or can only vote for one person in a slate of political
candidate (in most electoral systems). We introduce the weighted
generalized annotated program (wGAP) framework for expressing
competitive diffusion models. Applications are interested in the
eventual results from multiple competing diffusion models (e.g.
what is the likely number of sales of a given product, or how
many people will support a particular candidate). We define the
“most probable interpretation” (MPI) problem which technically
formalizes this need. We develop algorithms to efficiently solve
MPI and show experimentally that our algorithms work on
graphs with millions of vertices.

Annotated Probabilistic Temporal Logic: Approximate Fixpoint Implementation

by Paulo Shakarian

Paulo Shakarian, Gerardo I. Simari, V.S. Subrahmanian, ACM Transactions on Computational Logic, scheduled for Vol. 13, No. 2, 2011.

Annotated Probabilistic Temporal (APT) logic programs support building applications where we wish to reason about... more Annotated Probabilistic Temporal (APT) logic programs support building applications where we wish to reason about statements of the form “Formula G becomes true with a probability in the range [L,U] within (or in exactly)
t time units after formula F became true.” In this paper, we present a sound, but incomplete fixpoint operator that can be used to check consistency and entailment in APT logic programs. We present the first implementation of APT-logic programs and evaluate both its compute time and convergence on a suite of 23 ground APT-logic programs that were automatically learned from two real-world data sets. In both cases, the APT-logic programs contained up to 1,000 ground rules. In one data set, entailment problems were solved on average in under 0.1 seconds per ground rule, while in the other, it took up to 1.3 seconds per ground rule. Consistency was also checked in a reasonable amount of time. When discussing entailment of APT-logic formulas, convergence of the fixpoint operator refers to (U − L) being below a certain threshold. We show that on virtually all of the 23 automatically generated APT-logic programs, convergence was quick — often in just 2-3 iterations of the fixpoint operator. Thus, our implementation is a practical first step towards checking consistency and entailment in temporal probabilistic logics without independence or Markovian assumptions.