An Architecture for Integrating Concurrency Control into Environment Frameworks

Research in layered and componentized systems shows the benefit of dividing the responsibility of services into separate components. It is still an unresolved issue, however, how a system can be created from a set of existing (independently developed) components. This issue of integration is of immense concern to software architects since a proper solution would reduce duplicate implementation efforts and promote component reuse. In this paper we take a step towards this goal within the domain of software development environments (SDEs) by showing how to integrate an external concurrency control component, called Pern, with environment frameworks. We discuss two experiments where we integrated Pern with Oz, a multi-site, decentralized process centered environment, and Process WEAVER, a commercial process server. We introduce an architecture for retrofitting an external concurrency control component into an environment

Expanding the Repertoire of Process-based Tool Integration

The purpose of this thesis is to design and implement a new protocol for tool enveloping, in the context of the Oz Process Centered Environment. This new part of the system would be complementary to the already existing Black Box protocol for Oz and would deal with additional families of tools, whose character would be better serviced by a different approach, providing enhanced flexibility and a greater amount of interaction between the human operator, the tools and the environment during the execution of the wrapped activities. To achieve this, the concepts of persistent tool platforms, tool sessions and transaction-like activities will be introduced as the main innovative features of the protocol. We plan to be able to encapsulate and service conveniently classes of tools such as interpretive systems, databases, medium and large size applications that allow for incremental binding of parameters and partial retrieving of results, and possibly multi-user tools. Marginal modification and upgrading of the Oz general architecture and components will necessarily be performed

The agent architecture InteRRaP : concept and application

One of the basic questions of research in Distributed Artificial Intelligence (DAI) is how agents have to be structured and organized, and what functionalities they need in order to be able to act and to interact in a dynamic environment. To cope with this question is the purpose of models and architectures for autonomous and intelligent agents. In the first part of this report, InteRRaP, an agent architecture for multi-agent systems is presented. The basic idea is to combine the use of patterns of behaviour with planning facilities in order to be able to exploit the advantages both of the reactive, behaviour-based and of the deliberate, plan-based paradigm. Patterns of behaviour allow an agent to react flexibly to changes in its environment. What is considered necessary for the performance of more sophisticated tasks is the ability of devising plans deliberately. A further important feature of the model is that it explicitly represents knowledge and strategies for cooperation. This makes it suitable for describing high-level interaction among autonomous agents. In the second part of the report, the loading-dock domain is presented, which has been the first application the InteRRaP agent model has been tested with. An automated loading-dock is described where the agent society consists of forklifts which have to load and unload trucks in a shared, dynamic environment

Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

Integrating, Customizing, and Extending Environments with a Message-Based Architecture

Message-based architectures have typically been used for integrating an engineer‘s set of tools as in FIELD and SoftBench. This paper presents our experience using a message-based architecture to integrate complex, multi-user environments. Where this style of control integration has been effective for encapsulating independent tools within an environment, we show that these techniques are also useful for integrating environments themselves. Our experience comes from our integration of two types of process-centered software development environments: a groupware application that implements a Fagan-style code inspection process and a software development process environment where code inspection is a single step in the overall process. We use a message-based mechanism to federate the two process engines such that the two process formalisms complement rather than compete with each other. Moreover, we see that the two process engines can provide some synergy when used in a single, integrated software process environment, Specifically, the integrated environment uses the process modeling and enactment services of one process engine to customize and extend the code inspection process implemented in a different process engine. The customization and extension of the original collaborative application was accomplished without modifying the application. This was possible because the integration mechanism was designed for multi-user, distributed evironments and encouraged the use of an environment‘s services by other environments. The results of our study indicate that the message-based architecture originally conceived for tool-oriented control integration is equally well-suited for environment integration