Steve Munroe

The provenance of electronic data

It would include details of the processes that produced electronic data as far back as the beginning of time or at least the epoch of provenance awareness.

Security issues in a SOA-Based provenance system

Recent work has begun exploring the characterization and utilization of provenance in systems based on the Service Oriented Architecture (such as Web Services and Grid based environments). One of the salient issues related to provenance use within any given system is its security. Provenance presents some unique security requirements of its own, which are additionally dependent on the architectural and environmental context that a provenance system operates in. We discuss the security considerations pertaining to a Service Oriented Architecture based provenance system. Concurrently, we outline possible approaches to address them.

PrIMe: A methodology for developing provenance-aware applications

Provenance refers to the past processes that brought about a given (version of an) object, item or entity. By knowing the provenance of data, users can often better understand, trust, reproduce, and validate it. A provenance-aware application has the functionality to answer questions regarding the provenance of the data it produces, by using documentation of past processes. PrIMe is a software engineering technique for adapting application designs to enable them to interact with a provenance middleware layer, thereby making them provenance-aware. In this article, we specify the steps involved in applying PrIMe, analyze its effectiveness, and illustrate its use with two case studies, in bioinformatics and medicine.

Crossing the agent technology chasm: Lessons, experiences and challenges in commercial applications of agents

Agent software technologies are currently still in an early stage of market development, where, arguably, the majority of users adopting the technology are visionaries who have recognized the long-term potential of agent systems. Some current adopters also see short-term net commercial benefits from the technology, and more potential users will need to perceive such benefits if agent technologies are to become widely used. One way to assist potential adopters to assess the costs and benefits of agent technologies is through the sharing of actual deployment histories of these technologies. Working in collaboration with several companies and organizations in Europe and North America, we have studied deployed applications of agent technologies, and we present these case studies in detail in this paper. We also review the lessons learnt, and the key issues arising from the deployments, to guide decision-making in research, in development and in implementation of agent software technologies.

Learning and the evolution of language: the role of cultural variation and learning costs in the Baldwin effect

The Baldwin effect has been explicitly used by Pinker and Bloom as an explanation of the origins of language and the evolution of a language acquisition device. This article presents new simulations of an artificial life model for the evolution of compositional languages. It specifically addresses the role of cultural variation and of learning costs in the Baldwin effect for the evolution of language. Results show that when a high cost is associated with language learning, agents gradually assimilate in their genome some explicit features (e.g., lexical properties) of the specific language they are exposed to. When the structure of the language is allowed to vary through cultural transmission, Baldwinian processes cause, instead, the assimilation of a predisposition to learn, rather than any structural properties associated with a specific language. The analysis of the mechanisms underlying such a predisposition in terms of categorical perception supports Deacons hypothesis regarding the Baldwinian inheritance of general underlying cognitive capabilities that serve language acquisition. This is in opposition to the thesis that argues for assimilation of structural properties needed for the specification of a full-blown language acquisition device.

Commercial applications of agents: lessons, experiences and challenges

As has been argued very eloquently and effectively, there is a chasm that needs to be crossed in the adoption of any new technology [8], and the marketing of such technologies must somehow try to bridge the gap that arises. Many currently see agent technologies in the middle of that chasm period of adoption, where addressing the visionaries as well as the pragmatists (or early adopters) who avoid risks but readily see the advantages of tested technologies [11], is necessary. As part of the needed marketing exercise, we believe that a catalogue of case studies of deployed applications with real quantified business benefit, can help convince those wavering pragmatists. Perhaps more importantly, the lessons that can be drawn from such case studies may also be used to guide the efforts of new commercial agent technology providers, both in developing the technology itself, and in understanding the concerns and constraints of early adopters.

Autonomy: Variable and generative

In the paper we discuss variable and generative forms of autonomy. Variable autonomy is discussed in terms of the practicalities in designing autonomous agents, dealing as it does with the notion of degrees of autonomy and hence issues of agent control. The major part of the paper discusses an absolute, theoretically grounded notion of autonomy: the ability to generate ones own goals. This theoretical account of autonomy is embedded in the larger SMART framework and is intimately linked with the issue of motivation. Autonomous agents are motivated agents in that for the generation of goals an agent needs a set of higher order, non-derivative sources of action, or in our terminology, motivations. Autonomous agents in the SMART framework form the basis and source of action in multi-agent systems, which can thus propagate through the other entities in the system, such as non-autonomous agents and objects. We conclude with a discussion regarding the situations an autonomous agent would be willing to relinquish its autonomy thus linking the generative and variable notions of autonomy.

PrIMe: a software engineering methodology for developing provenance-aware applications

Provenance is a concept often used in the Art world to refer to the documented history of an artifact, providing information about the artifacts lineage and authenticity. Provenance-aware applications similarly allow their users to have confidence about the data they produce, and can enable users to make judgements relating to notions of trust, accountability, validation, replication and compliance of their data. PrIMe is a software engineering methodology for adapting applications to enable them to interact with a provenance middleware layer, thereby making them provenance-aware. Such applications allow users to answer questions about provenance use cases, which are descriptions of scenarios in which a user interacts with a system by performing particular functions on that system. In order to illustrate how PrIMe can make applications provenance-aware, an Organ Transplant Management example application is used.

AAMAS '05: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems

The ability to create reliable, scalable virtual organisations (VOs) on demand in a dynamic, open and competitive environment is one of the challenges that underlie Grid computing. In response, in the CONOISE-G project, we are developing an infrastructure to support robust and resilient virtual organisation formation and operation. Specifically, CONOISE-G provides mechanisms to assure effective operation of agent-based VOs in the face of disruptive and potentially malicious entities in dynamic, open and competitive environments. In this paper, we describe the CONOISE-G system, outline its use in VO formation and perturbation, and review current work on dealing with unreliable information sources.

Modelling the provenance of data in autonomous systems

Determining the provenance of data, i.e. the process that led to that data, is vital in many disciplines. For example, in science, the process that produced a given result must be demonstrably rigorous for the result to be deemed reliable. A provenance system supports applications in recording adequate documentation about process executions to answer queries regarding provenance, and provides functionality to perform those queries. Several provenance systems are being developed, but all focus on systems in which the components are reactive, for example Web Services that act on the basis of a request, job submission system, etc. This limitation means that questions regarding the motives of autonomous actors, or agents, in such systems remain unanswerable in the general case. Such questions include: who was ultimately responsible for a given effect, what was their reason for initiating the process and does the effect of a process match what was intended to occur by those initiating the process? In this paper, we address this limitation by integrating two solutions: a generic, re-usable framework for representing the provenance of data in service-oriented architectures and a model for describing the goal-oriented delegation and engagement of agents in multi-agent systems. Using these solutions, we present algorithms to answer common questions regarding responsibility and success of a process and evaluate the approach with a simulated healthcare example.