Álvaro F. Moreira

Proving BDI Properties of Agent-Oriented Programming Languages

In this paper, we consider each of the nine BDI principles defined by Rao and Georgeff based on Bratmans asymmetry thesis, and we verify which ones are satisfied by Raos AgentSpeak(L), a logic programming language inspired by the BDI architecture for cognitive agents. In order to set the grounds for the proofs, we first introduce a rigorous way in which to define the informational, motivational, and deliberative modalities of BDI logics for AgentSpeak(L) agents, according to its structural operational semantics that we introduced in a recent paper. This computationally grounded semantics for the BDI modalities forms the basis of a framework that can be used to further investigate BDI properties of AgentSpeak(L) agents, and contributes towards establishing firm theoretical grounds for a BDI approach to agent-oriented programming.

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.

Temporal and versioning model for schema evolution in object-oriented databases

In this paper we define the Temporal and Versioning Model for Schema Evolution (TVSE), a model that uses time and version concepts to manage dynamic schema evolution in object-oriented databases. The proposed model is able to manage the schema evolution process considering: schema versioning, schema modification, change propagation and data manipulation. TVSE differs from other schema evolution models by enabling the homogeneous and simultaneous management of the evolution history concerning both intentional and extensional databases. Besides defining the model, we also propose a language to derive and modify schema versions, and also to update data associated with them, creating either new object versions or just keeping the history of these data modifications. We provide an operational semantics for this language which is an essential step towards for establishing the preservation of complex time integrity constraints.

Proving the Asymmetry Thesis Principles for a BDI Agent-Oriented Programming Language

Abstract In this paper, we consider each of the nine principles of BDI logics as defined by Rao and Georgeff based on Bratmans asymmetry thesis, and we verify which ones are satisfied by Raos AgentSpeak(L), a computable logic language inspired by the BDI architecture for cognitive agents. This is in line with Raos original motivation for defining AgentSpeak(L): to bridge the gap between the theory and practice of BDI agent systems. In order to set the grounds for the proof, we first introduce a particular way in which to define the informational, motivational, and deliberative modalities of BDI logics for AgentSpeak(L) agents, according to its structural operational semantics (that we introduced in a recent paper). This provides a framework that can be used to investigate further properties of AgentSpeak(L) agents, contributing towards giving firm theoretical grounds for BDI agent programming.

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.

Ontology reasoning in agent-oriented programming

DL-Lite is being regarded as an effective logic for ontology reasoning due both to its expressive power and its computational properties. Considering that ontologies are important constructs for multi-agent system, in this paper we propose the integration of ontology reasoning and agent-oriented programming. More specifically, we consider an agent-oriented programming language based on DL-Lite with belief bases consisting of an immutable TBox, with the characterization of concepts and roles, and of an ABox with factual knowledge, which can change as the result of perception of the environment, internal actions, and inter-agent communication. We discuss the benefits of ontological reasoning and we give algorithms for belief base querying, plan selection, and for a principled approach for belief base update. The language we propose, AgentSpeak-DL, is a subset of AgentSpeak, a well known BDI multi-agent oriented programming language.

An Agent-Oriented Programming Language for Computing in Context

Context aware intelligent agents are key components in the development of pervasive systems. In this paper, we present an extension of a BDI programming language to support ontological reasoning and ontology-based speech act communication. These extensions were guided by the new requirements brought about by such emerging computing styles. These new features are essential for the development multi-agent systems with context awareness, given that ontologies have been widely pointed out as an appropriate way to model contexts.

Identifying business rules to legacy systems reengineering based on BPM and SOA

Legacy systems include information and procedures which are fundamental to the organization. However, to maintain a legacy system is a complex and expensive task. Currently, researches propose the legacy systems reengineering using BPM and SOA. The benefits of the reengineering using BPM and SOA are software reuse and documentation of the business processes. However, practical experiences demonstrate that reengineering using BPM and SOA are not easy to apply, because there are no tools that help the developers understand the legacy system behavior. This paper presents a tool to extract the legacy system behavior. Based on the business rules concept, we propose a tool to identify the business rules contained legacy source code. In addition, our technique also enables the discovery of the partial order execution of the business rules during the runtime legacy system.

Compiler Optimizations Do Impact the Reliability of Control-Flow Radiation Hardened Embedded Software

This paper characterizes how compiler optimizations impact software control-flow reliability when the optimized application is compiled with a technique to enable the software itself to detect and correct radiation induced soft-errors occurring in branches. Supported by a comprehensive fault injection campaign using an established benchmark suite in the embedded systems domain, we show that the careful selection of the available compiler optimizations is necessary to avoid a significant decrease of software reliability while sustaining the performance boost those optimizations provide.

Bit-Flip Aware Control-Flow Error Detection

Recent increase of transient fault rates has made processor reliability a major concern. Moreover performance improvements are required for many of todays embedded systems. At the same time software implemented fault detection remains the only option for off-the-shelf processors. Software methods, however, introduce significant performance overheads due to the additional instructions required for the detection. A good observation is that often code segments not susceptible to faults are protected. In this paper we propose a technique for systematic analysis of the bit-flip effects on the program control-flow in order to identify only those locations susceptible to control-flow errors and hence minimize the number of fault detection assertions. We instrument the code with minimal overhead, while maintaining high fault coverage level. Our experiments show that using the result of our bit-flip analysis and limiting the code instrumentation to only the susceptible locations releases 28.9% (on average) of the memory while the level of fault coverage remains the same as with full instrumentation.