Rem W. Collier

Agent factory micro edition: a framework for ambient applications

Ambient Intelligence represents a vision of the future whereby the world will be saturated with embedded electronic devices that are sensitive and responsive to people. This technology will combine the concepts of intelligent systems with that of pervasive computing. Intelligent agents of varying capabilities will provide the foundations for many applications within this domain. As a means of achieving this objective a framework – Agent Factory Micro Edition (AFME) has been developed to enable the creation of agent-based applications on computationally constrained devices such as cellular digital mobile phones. It has been specifically designed to tackle the performance and memory footprint issues associated with executing intentional agents on mobile devices.

ProbFuse: a probabilistic approach to data fusion

Data fusion is the combination of the results of independent searches on a document collection into one single output result set. It has been shown in the past that this can greatly improve retrieval effectiveness over that of the individual results.This paper presents probFuse, a probabilistic approach to data fusion. ProbFuse assumes that the performance of the individual input systems on a number of training queries is indicative of their future performance. The fused result set is based on probabilities of relevance calculated during this training process. Retrieval experiments using data from the TREC ad hoc collection demonstrate that probFuse achieves results superior to that of the popular CombMNZ fusion algorithm.

AF-APL – bridging principles and practice in agent oriented languages

For AOP (Agent Oriented Programming) to become a mature discipline, lessons must be learned from practical language implementations. We present AF-APL (AgentFactory – Agent Programming Language) as an Agent Oriented Programming Language that has matured with continued revisions and implementations, resulting in a language – which, although based on the more theoretical aspects of AO design – has incorporated many of the practical considerations of programming real world agents. We describe AF-APL informally, focusing on its experience driven features, such as commitment reasoning, a rich plan operator set, and an inherent asynchronous design. We present the default execution cycle for the AF-APL interpreter, looking in detail at the Commitment Management model. This model provides an agent with power to reason about its own actions, while maintaining basic constraints on computational tractability. In our development of the language, we learned many lessons that are not covered in the purer AO language definitions. Before concluding, we discuss a number of these lessons.

Towards Pervasive Intelligence: Reflections on the Evolution of the Agent Factory Framework

Agent Factory is a cohesive framework for the development and deployment of multi-agentsystems. Since its inception in the mid 1990s, Agent Factory has gone through a metamorphosis process, whereby several new extensions, revisions, and enhancements have been made. This chapter provides a discussion of the incremental developments in Agent Factory and provides motivations as to why such changes were necessary. Agent Factory distinguishes itself from other intentional agent platforms in several ways. It provides a practical and efficient approach to the development of intentional agent-oriented applications. This is combined with a methodology, integrated development environment support, and a suite of tools that aid the agent fabrication process. Adetailed comparison to related work is provided. We include a tutorial on how to use the framework.

Debugging agents in agent factory

The ability to effectively debug agent-oriented applications is vital if agent technologies are to become adopted as a viable alternative for complex systems development. Recent advances in the area have focussed on the provision of support for debugging agent interaction where tools have been provided that allow developers to analyse and debug the messages that are passed between agents. One potential approach for constructing agent-oriented applications is through the use of agent programming languages. Such languages employ mental notions such as beliefs, goals, commitments, and intentions to facilitate the construction of agent programs that specify the high-level behaviour of the agent. This paper describes how debugging has been supported for one such language, namely the Agent Factory Agent Programming Language (AFAPL).

ACCESS: An Agent Architecture for Ubiquitous Service Delivery

This paper introduces the Agents Channeling ContExt Sensitive Services (ACCESS) architecture, an agent-based architecture that supports the development and deployment of context sensitive services. Specifically, ACCESS is comprised of two sub-systems: a run-time system that delivers the minimum functionality necessary to execute ACCESS Agents, and a development environment that delivers structured tool-based support for the creation, development, and visualization of u-commerce services.

Sensor Web interaction

Ubiquitous sensing fuses the concepts of intelligent systems with ubiquitous computing in the development of novel Sensor Web applications, whereby the interaction of multiple disparate autonomous artefacts is a key requirement. In this paper, we present SIXTH, which is a middleware infrastructure for Ubiquitous Sensing that facilitates, and supports, the development and deployment of Sensor Web applications. SIXTH has been designed to be extensible, with provisions for user definable data retention policies, custom sensor data representations, and custom sensor node representations, whilst still providing a rich set of default behaviours. Within SIXTH, support is provided for the development and interaction of applications that incorporate both physical and cyber (virtual server side) sensors. With a view to supporting intelligent, in network, interaction policies, whereby sensor nodes must negotiate and coordinate their behaviour, the system has been designed to operate in conjunction with Agent Factory Micro Edition (AFME). AFME is a minimised footprint intelligent agent platform designed for resource constrained devices. It is based on the standard Agent Factory platform, which was developed for desktop machines, and is representative of a class of agent systems, which are referred to as Agent Oriented Programming frameworks. The paper discusses a ubiquitous mapping application that was developed using the middleware.

SoSAA: a framework for integrating components & agents

Modern computing systems require powerful software frameworks to ease their development and manage their complexity. These issues are addressed within both Component-Based Software Engineering and Agent-Oriented Software Engineering, although few integrated solutions exist. This paper discusses a novel integration strategy, which builds upon both paradigms to address their shortcomings while leveraging their different characteristics to define a complete software framework.

A Balanced Energy-Efficient Multihop clustering scheme for Wireless Sensor Networks

Network lifetime is crucial in Wireless Sensor Network (WSN) systems since recharging or exchanging the sensors is difficult and expensive. Clustering techniques provide an interface for WSN topology management to extend network lifetime. Existing clustering algorithms, such as LEACH and HEED, can significantly reduce the power consumption on each sensor and thus prolong the network lifetime. However, most existing work fails to consider the coverage of the network when evaluating the lifetime of a network. An advanced clustering algorithm should not only be able to extend the longevity, but also maintain the coverage. We believe that evening the load in every unit area rather than on each single sensor can provide better-balanced power usage through the network. Although it is hard to achieve perfectly balanced load, the sensors that are still alive should be well distributed over the sensing area. In this paper, we propose a novel algorithm based on HEED, named the Balanced Energy-Efficiency (BEE) clustering algorithm. Experimental results show that BEE exceeds HEED and LEACH from two perspectives: 1) longevity and 2) balanced sensor distribution. It can guarantee the network coverage for a longer time, compared with HEED and LEACH. We also illustrate the multihop version of BEE, called the Balanced Energy-Efficiency Multihop (BEEM) clustering algorithm, which can further improve the performance of BEE.

Decision-making of BDI agents, a fuzzy approach

This paper introduces and proposes agent fuzzy decision-making (AFDM), as an extension to the classical belief-desire-intention (BDI) model. AFDM addresses the limitations of present formalisms within BDI models by making decisions based on quantified fuzzy judgment. The AFDM matrix model enables quantitative calculation and thus, provides a more practical solution to BDI models. In addition, more flexible and controllable solutions to BDI persistence can be expected with the introduction of AFDM.