CRAFTING THE MIND OF PROSOCS AGENTS

PROSOCS agents are software agents that are built according to the KGP model of agency. KGP is used as a model for the mind of the agent, so that the agent can act autonomously using a collection of logic theories, providing the mind's reasoning functionalities. The behavior of the agent is controlled by a cycle theory that specifies the agent's preferred patterns of operation. The implementation of the mind's generic functionality in PROSOCS is worked out in such a way so it can be instantiated by the platform for different agents across applications. In this context, the development of a concrete example illustrates how an agent developer might program the generic functionality of the mind for a simple application. 20 2-4 105 131 Cited By :1

Narrative based Postdictive Reasoning for Cognitive Robotics

Making sense of incomplete and conflicting narrative knowledge in the presence of abnormalities, unobservable processes, and other real world considerations is a challenge and crucial requirement for cognitive robotics systems. An added challenge, even when suitably specialised action languages and reasoning systems exist, is practical integration and application within large-scale robot control frameworks. In the backdrop of an autonomous wheelchair robot control task, we report on application-driven work to realise postdiction triggered abnormality detection and re-planning for real-time robot control: (a) Narrative-based knowledge about the environment is obtained via a larger smart environment framework; and (b) abnormalities are postdicted from stable-models of an answer-set program corresponding to the robot's epistemic model. The overall reasoning is performed in the context of an approximate epistemic action theory based planner implemented via a translation to answer-set programming.Comment: Commonsense Reasoning Symposium, Ayia Napa, Cyprus, 201

A Framework for Grid-Enabling Scientific Workflow Systems. Architecture and application case studies on interoperability and heterogeneity in support for Grid workflow automation.

Since the early 2000s, Service Oriented Architectures (SOAs) have played a key role in the development of complex applications within a virtual organization (VO) context. Grids and workflows have emerged as vital technologies for addressing the (SOA) paradigm. Given the variety of Grid middleware, scientific workflow systems and Grid workflows available, bringing the two technologies together in a flexible, reusable and generalized way has been largely overlooked, particularly from a scientific end user perspective. The lack of domain focus in this area has led to a slow uptake of Grid technologies. This thesis aims to design a framework for Grid-enabling workflows, which identifies the essential technological components, how these components fit together in layered architecture and the interactions between them. To produce such a framework, this thesis first investigates the definition of a Grid-workflow architecture and mapping Grid functionality to workflow nodes, focusing on striking a balance between performance, usability and the Grid functionality supported. Next, it presents an examination of framework extensions for supporting various forms of Grid heterogeneity, essential for ii VO based collaboration. Given the complex nature of Grid technologies, the work presented here investigates abstracting Grid based workflows through high-level definitions and resolution using semantic technologies. Finally, this thesis presents a way to resolves abstract Grid workflows using semantic technologies and intelligent, autonomous agents. The frameworks presented in this thesis are tested and evaluated within the context of domain-based case studies defined in the SIMDAT, BRIDGE and ARGUGRID EU funded research projects