Renata Vieira

An empirically based system for processing definite descriptions

We present an implemented system for processing definite descriptions in arbitrary domains. The design of the system is based on the results of a corpus analysis previously reported, which highlighted the prevalence of discourse-new descriptions in newspaper corpora. The annotated corpus was used to extensively evaluate the proposed techniques for matching definite descriptions with their antecedents, discourse segmentation, recognizing discourse-new descriptions, and suggesting anchors for bridging descriptions.

Jason and the Golden Fleece of Agent-Oriented Programming

This chapter describes Jason, an interpreter written in Java for an extended version of AgentSpeak, a logic-based agent-oriented programming language that is suitable for the implementation of reactive planning systems according to the BDI architecture. We describe both the language and the various features and tools available in the platform.

Resolving bridging references in unrestricted text

Our goal is to develop a system capable of treating the largest possible subset of definite descriptions in unrestricted written texts. A previous prototype resolved anaphoric uses of definite descriptions and identified some types of first-mention uses, achieving a recall of 56%. In this paper we present the latest version of our system, which handles some types of bridging references, uses WordNet as a source of lexical knowledge, and achieves a recall of 65%.

Extending the Operational Semantics of a BDI Agent-Oriented Programming Language for Introducing Speech-Act Based Communication

Work on agent communication languages has since long striven to achieve adequate speech act semantics; partly, the problem is that references to an agent’s architecture (in particular a BDI-like architecture) would be required in giving such semantics more rigorously. On the other hand, BDI agent-oriented programming languages have had their semantics formalised for abstract versions only, neglecting practical aspects such as communication primitives; this means that, at least in what concerns communication, implementations of BDI programming languages have been ad hoc. This paper tackles, however preliminarily, both these problems by giving semantics to speech-act based messages received by an AgentSpeak(L) agent. AgentSpeak(L) is a BDI, agent-oriented, logic programming language for which interpreters have been developed, and its theoretical foundations are of great interest. Our work here builds upon a structural operational semantics to AgentSpeak(L) that we have given in previous work. The contribution of this paper is two-fold: we here extend our earlier work on providing a solid theoretical background on which to base existing implementations of AgentSpeak(L) interpreters, as well as we shed light on a more computationally grounded approach to giving semantics for some key illocutionary forces used in speech-act based agent communication languages.

A cooperative approach for composite ontology mapping

This paper proposes a cooperative approach for composite ontology mapping. We first present an extended classification of automated ontology matching and propose an automatic composite solution for the matching problem based on cooperation. In our proposal, agents apply individual mapping algorithms and cooperate in order to change their individual results. We assume that the approaches are complementary to each other and their combination produces better results than the individual ones. Next, we compare our model with three state of the art matching systems. The results are promising specially for what concerns precision and recall. Finally, we propose an argumentation formalism as an extension of our initial model. We compare our argumentation model with the matching systems, showing improvements on the results.

Agent-Oriented programming with underlying ontological reasoning

Developing applications that make effective use of machine-readable knowledge sources as promised by the Semantic Web vision is attracting much of current research interest; this vision is also affecting important trends in computer science such as grid-based and ubiquitous computing. In this paper, we formally define a version of the BDI agent-oriented programming language AgentSpeak based on description logic rather than predicate logic. In this approach, the belief base of an agent contains the definition of complex concepts, besides specific factual knowledge. We illustrate the approach using examples based on the well-known smart meeting-room scenario. The advantages of combining AgentSpeak with description logics are: (i) queries to the belief base are more expressive as their results do not rely only on explicit knowledge but can be inferred from the ontology; (ii) the notion of belief update is refined given that (ontological) consistency of a belief addition can be checked; (iii) retrieving a plan for handling an event is more flexible as it is not based solely on unification but on the subsumption relation between concepts; and (iv) agents may share knowledge by using ontology languages such as OWL. Extending agent programming languages with description logics can have a significant impact on the development of multi-agent systems for the semantic web.

In silico network topology-based prediction of gene essentiality

The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on the network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision-tree-based machine-learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision-tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering the essential genes in Escherichia coli and then assessed its performance.

Multilingual Corpora Annotation for Processing Definite Descriptions

This paper presents a multilingual corpora study aimed to verify the applicability of heuristics developed for coreference resolution in English texts to Portuguese and French language.

Towards resolution of bridging descriptions

We present preliminary results concerning robust techniques for resolving bridging definite descriptions. We report our analysis of a collection of 20 Wall Street Journal articles from the Penn Treebank Corpus and our experiments with WordNet to identify relations between bridging descriptions and their antecedents.

An extended value-based argumentation framework for ontology mapping with confidence degrees

Heuristics to combine different approaches for ontology mapping have been proposed in the literature. This paper proposes to use abstract argumentation frameworks to combine such approaches. We extend the Value-based Argumentation Framework (VAF)[2], in order to represent arguments with confidence degrees. Our agents apply individual mapping algorithms and cooperate in order to exchange their local results (arguments). Next, based on their preferences and confidence of the arguments, the agents compute their preferred mapping sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments.