Here - Agents Lab - University of Nottingham

However, while having multiple options is a potential source of robustnessand adaptability, the combinatorial growth of possible execution traces makesdifficult to scale to complex ecologies. Adapting, within tractable time frames, todynamically changing goals and environmental conditions is made more challengingwhen these conditions fall outside those envisioned by the system designer.In the EU FP7 project RUBICON (Robotic UBIquitous COgnitive Network)[1][2] we tackle these challenges by seeking to develop goal-oriented robotic ecologiesthat exhibit a tightly coupled, self-sustaining learning interaction among allof their participants. Specifically, we investigate how all the participants in theRUBICON ecology can cooperate in using their past experience to improve theirperformance by autonomously and proactively adjusting their behaviour andperception capabilities in response to a changing environment and user needs.An important pre-requisite of such an endeavour, which is addressed in thispaper, is the necessary software infrastructure subtending the specification, integration,and the distributed management of the operations of robotic ecologies.Specifically, this work builds upon the Self -OSGi [3] [4], a modular andlightweight agent system built over Java technology from the Open Service GatewayInitiative (OSGi) [5], and extends it to operate across distributed platformsby integrating it with the PEIS middleware, previously developed as part ofthe Ecologies of Physically Embedded Intelligent Systems project [6]. The resultdescribed in this paper is a distributed programming framework for the specificationand the development of robotic ecologies.The remainder of the paper is organized in the following manner: Section 2provides an overview of the state of the art techniques for the coordination ofrobotic ecologies, with an emphasis on those pursued within the PEIS initiative- the starting point for the control of RUBICON robotic ecologies. Section 3presents the Self -OSGi component & service-based agent framework, and theway it has been recently extended and integrated with PEIS. Section 4 illustratesthe use of the resulting multi-agent framework with a robotic ecology experiment.Finally, Section 5 summarizes the contributions of this paper and points to someof the directions to be explored in future research.2 PEISThe PEIS kernel [7] and related middleware tools are a suite of software, previouslydeveloped as part of the PEIS project [6] in order to enable communicationand collaboration between heterogeneous robotic devices.The PEIS kernel is written in pure C (with binding for Java and other languages)and with as few library and RAM/processing dependencies as possiblein order to fit on a wide range of devices.PEIS includes a decentralized mechanism for collaboration between separateprocesses running on separate devices that allows for automatic discovery, highlevelcommunication and collaboration through subscription based connections.It also offers a shared, tuple space blackboard that allows for high level collaborationand dynamic self-configuration between different devices through the70