We present a qualitative study that examines how aged and community care professionals conceptualise generative AI applications, with particular attention to issues of agency, ethics, and emergent practices and behaviours. There is a growing body of research describing individual AI applications, their effectiveness and ethical implications. However, multiple applications of AI could more radically distort service boundaries and change provider practices for collaborative human-AI teams. Little is known about practitioners’ desired future roles and values for human-AI implementations and possible service innovations. Changes driven by care providers, AI service providers and government policies will have significant implications for complex settings such as aged care and community care. Through seven focus groups employing multiple qualitative methods, we identify coherence and gaps between theoretical and practitioner perspectives on the uses and implications of generative AI. Our findings suggest an urgent need for education and research to bridge theory and practical understanding of generative AI in aged and community care settings and policies to ensure marginalised groups are not locked out of future care services and models.

Technologies can support the well-being of people living with dementia in residential care by fostering meaningful interactions through multimodal and playful features. This article presents the evaluation of A Better Visit, an app that aims at engaging residents and visitors in shared activities. We define engagement in terms of dyadic interactions with the interface of the device, and interactions within the social context of the care home. We generated two Motivational Models that describe different perspectives of how people engaged with the system: the first was built with the design team, and the second was built using the first Motivational Model as a sensitising concept for the analysis of data from four care homes that used the app for periods of three months. Our findings show that the facilitation of activities plays a relevant role for engaging in social interaction. We discuss how technologies can contribute to engaging people living with dementia in social interaction: firstly, facilitation can be understood as a concept that is supported by people and technology. Secondly, we discuss the influence of the social context of the setting and the understandings of the individual in how people assess the engagement of the residents in social interaction.

Requirements engineering involves the elicitation, representation and communication of diverse stakeholder needs. However, this can be particularly challenging when developing technology embedded within complex social systems. So-called socially-oriented requirements can be abstract, ambiguous and driven by the organisational, cultural and political contexts of the stakeholders involved. Motivational models are one solution which supports project-wide understanding of the key goals of stakeholders. Yet, there is still a lack of understanding about the role they can play in larger industrial projects. We present our use of motivational modelling in an Australia-wide project that develops new technology to assist people who are homeless in accessing service providers. We interviewed 100 stakeholders and utilised motivational models to advocate for the needs of key stakeholder groups. We discuss the benefits, challenges and lessons learned.

Socially assistive robots (SARs) offer great promise for improving outcomes in paediatric rehabilitation. However, the design of software and interactive capabilities for SARs must be carefully considered in the context of their intended clinical use. While previous work has explored specific roles and functionalities to support paediatric rehabilitation, few have considered the design of such capabilities in the context of ongoing clinical deployment. In this article, we present a two-phase in situ design process for SARs in health care, emphasising stakeholder engagement and on-site development. We explore this in the context of developing the humanoid social robot NAO as a socially assistive rehabilitation aid for children with cerebral palsy. We present and evaluate our design process, outcomes achieved, and preliminary results from ongoing clinical testing with 9 patients and 5 therapists over 14 sessions. We argue that our in situ design methodology has been central to the rapid and successful deployment of our system.

In this paper, we describe research results arising from a technology transfer exercise on agent-oriented requirements engineering with an industry partner. We introduce two improvements to the state-of-the-art in agent-oriented requirements engineering, designed to mitigate two problems experienced by ourselves and our industry partner: (1) the lack of systematic methods for agent-oriented requirements elicitation and modelling; and (2) the lack of prescribed deliverables in agent-oriented requirements engineering. We discuss the application of our new approach to an aircraft turnaround simulator built in conjunction with our industry partner, and show how agent-oriented models can be derived and used to construct a complete requirements package. We evaluate this by having three independent people design and implement prototypes of the aircraft turnaround simulator, and comparing the three prototypes. Our evaluation indicates that our approach is effective at delivering correct, complete, and consistent requirements that satisfy the stakeholders, and can be used in a repeatable manner to produce designs and implementations. We discuss lessons learnt from applying this approach.

Patterns have recorded the experience of engineering software systems. Various patterns have been introduced and described in several domains. A particular class of patterns, task knowledge patterns that are important for agent oriented software development, is investigated in this paper. It has been reported that descriptions of task knowledge given in the pattern literature is not clearly structured, and some of the useful description is left implicit to the developer. This paper reports our investigation on task knowledge that has been shared across a wider spectrum of articles to showcase such scenario. We present a new way to analyse and classify task knowledge patterns. Furthermore, we demonstrate how the experience of different development groups is described very differently based on the classification result. The investigation shows the need to present task descriptions in a structured manner. The analysis and classification techniques demonstrated are applicable for agent-based simulation.

A communication protocol is a fundamental component of a multi-agent system. The security requirements for a communication protocol should be articulated during the early stages of software development. However, there is no formal way provided for software developers to find out what makes a communication protocol secure and what are secure designs. In this paper we propose a method that defines security requirements, bridges security requirement analysis with security design, and integrates the security techniques into a communication protocol to fulfill the security requirements.

This paper presents experience with using a hybrid agent-oriented software engineering methodology for designing an agent-based software system. We elicit and analyse system requirements using ROADMAP, with associated tool REBEL. We develop initial system design using Prometheus with associated tool PDT. Applying the combination of the methodologies facilitates understanding of system requirements by non-technical clients. A key feature of our work is its handling of quality requirements, which are identified as an essential asset for analysing design alternatives. We contribute to the current state of art by demonstrating the application of a hybrid methodology with a case study of a smart music player. We created concrete artefacts to represent models and found and clarified conflicting concepts between the two methodologies when we developed the case study. Suggestions are proposed to facilitate goal elicitation and verification.

Future software systems will be intelligent and adaptive. They will have the ability to seamlessly integrate with smart applications that have not been explicitly designed to work together. Traditional software engineering approaches offer limited support for the development of intelligent systems. To handle the tremendous complexity and the new engineering challenges presented by intelligence, adaptiveness and seamless integration, developers need higher-level development constructs. Agent concepts are natural to describe intelligent adaptive systems. Agent-based technologies have been incorporating software engineering practices, and have matured to offer useful insights and concrete practices to mainstream software engineers.This tutorial presents the state of the art in agent development from a software engineering perspective, focusing on practices that are applicable today. We will walk the audience through analysis, design and verification of a portion of a real-world problem: a Smart Home Network. We show how agent concepts more naturally match the engineering challenges of such systems like trust between adaptive components. The audience will have hands-on experience with analyzing and designing parts of the Smart Home Network and learn how to incorporate agent technologies into their current projects.

Agent technology is increasingly being used to develop software systems in different domains. Hence particular design problems are recurring in different multiagent systems development projects. In order to enhance the reuse of proven solutions to recurring design problems, agent design patterns are being identified and documented. Understandably, most of the available work on agent design patterns reflect object oriented concepts (classes, objects, inheritance, etc) and exhibit an implementation bias. It is preferable for these patterns to reflect the notions of agency and be described at the right level of abstraction. In this paper, we present a new agent design pattern classification scheme that is structured to better reflect the notions of agency and allow varying levels of abstraction in describing agent design patterns. We also show how four different agent design patterns fit into our classification scheme.

The research field of Agent-Oriented Software Engineering (AOSE) aims to find abstractions, languages, methodologies and toolkits for modeling, verifying, validating and prototyping complex applications conceptualized as Multiagent Systems (MASs). A very lively research sub-field studies how formal methods can be used for AOSE. This paper presents a detailed survey of six logic-based executable agent specification languages that have been chosen for their potential to be integrated in our ARPEGGIO project, an open framework for specifying and prototyping a MAS. The six languages are $\textsf{ConGolog}$ , $\textsf{AGENT-0}$ , the $\textsf{IMPACT}$ agent programming language, $\textsf{DyLOG}$ , Concurrent $\textsf{METATEM}$ and ${\cal E}_{hhf}$ . For each executable language, the logic foundations are described and an example of use is shown. A comparison of the six languages and a survey of similar approaches complete the paper, together with considerations of the advantages of using logic-based languages in MAS modeling and prototyping.

Roles are an essential concept within agent-oriented software engineering (AOSE). Role definitions in current AOSE methodologies are usually claimed to be for use at the requirements level. However, in most methodologies, they are too low level, specifying too much detail. We present a "higher level" role specification. The role specification method described works together with other agent specification/analysis methods that we and others have developed. However, we believe that role specification may also be used with nonagent-based systems, and provide a useful abstraction for specifying the requirements of any software system.

Neural networks have been used to solve a wide range of problems. Unfortunately, many of the applications of neural networks reported in the literature have been built in an ad-hoc manner, without being informed by the techniques and tools of software engineering. The problem with developing neural networks in an ad-hoc manner, using a "trial and error" or "build and fix" approach, is that successes are difficult to repeat. Building neural networks to solve specific problems using ad-hoc processes is repeatable only if there is a sufficient culture of disciplined practice and experienced people in the organisation to facilitate the process. We propose a set of methods for developing neural networks that can be used to systematically and repeatably "engineer" neural networks to solve specific problems. We explore the "design problem "for neural networks, and the problem of validating and verifying the operation and learning algorithms for neural network software. A feature of our approach is to separate the generic components of a neural network from the application specific components.

This paper addresses issues faced by agents operating in large-scale multi-cultural environments. We argue for systems that are tolerant of heterogeneity. The discussion is illustrated with a running example of researching and comparing university web sites, which is a realistic scenario representative of many current knowledge management tasks that would benefit from agent assistance. We discuss efforts of the Intelligent Agent Laboratory toward designing such tolerant systems, giving a detailed presentation of the results of several implementations.

Computational logic systems can offer an attractive environment for developing Internet applications. They share many of the important characteristics of popular network programming tools, including dynamic memory management, well-behaved structure and pointer manipulation, robustness, and compilation to architecture-independent bytecode. However, in addition, computational logic systems offer some unique features such as very powerful symbolic processing capabilities, constraint solving, dynamic databases, search facilities, grammars, sophisticated meta-programming, and well understood semantics. Such features can often make it very easy to code simple applications. This special issue concerned with applications is the third of its kind in a journal sponsored by the Association for Logic Programming. The first appeared in 1990, and showed the potential for logic programming to be extended. The second issue highlighted some papers from the Practical Applications of Prolog conference that had been held. This third time, the applications are concerned with the Internet and reflect the profound impact that the Internet has had on the computing landscape.

The World Wide Web is a vast resource of information and services that continues to grow rapidly. How to find information providers and how to integrate information agents in such an open environment are new challenges. In this paper, we present an open multi-agent system called SportsAgents, for information gathering from the World Wide Web. In this system, middleware agents are introduced to solve the interoperability problem among information agents. Novel aspects in SportsAgents are an intelligent matchmaking algorithm for inferring the service relationships among information agents, and a naive Bayesian model for information agent cooperation formation is given. Information agents use score patterns to extract semi-structured sports results. All these make the system open and scalable to new applications and flexible for organising the agents' cooperation.

Achieving confidence in the correctness, completeness and consistency of requirements specifications can be problematic and the consequences of incorrect requirements can be costly. In this paper we argue that specification and animation can provide reasonably high levels of assurance in the requirements without the overheads of using general purpose theorem proving tools. We propose a framework based on mode analysis and the operational semantics of logic programs for animating specifications. The framework allows us to combine prototyping and limited forms of automated deduction to increase our levels of confidence in specifications. Finally, we show how such a framework can be used to increase the level of confidence in the correctness of a simple dependency management system specification written in Z.

Although case‐based reasoning (CBR) was introduced as an alternative to rule‐based reasoning (RBR), there is a growing interest in integrating it with other reasoning paradigms, including RBR. New hybrid approaches are being piloted to achieve new synergies and improve problem‐solving capabilities. In our approach to integration, CBR is used to satisfy multiple numeric constraints, and RBR allows the performance of “what if” analysis needed for creative design. The domain of our investigation is nutritional menu planning. The task of designing nutritious, yet appetizing, menus is one at which human experts consistently outperform computer systems. Tailoring a menu to the needs of an individual requires satisfaction of multiple numeric nutrition constraints plus personal preference goals and aesthetic criteria. We first constructed and evaluated independent CBR and RBR menu planning systems, then built a hybrid system incorporating the strengths of each system. The hybrid outperforms either single strategy system, designing superior menus, while synergistically providing functionality that neither single strategy system could provide. In this paper, we present our hybrid approach, which has applicability to other design tasks in which both physical constraints and aesthetic criteria must be met.

This paper introduces a design for agile manufacturing workcells intended for light mechanical assembly of products made from similar components (i.e. parts families). We define agile manufacturing as the ability to accomplish rapid changeover from the assembly of one product to the assembly of another product. Rapid hardware changeover is made possible through the use of robots, flexible part feeders, modular grippers and modular assembly hardware. The flexible feeders rely on belt feeding and binary computer vision for Dose estimation. This has a distinct advantage over non-flexible feeding schemes such as bowl feeders which require considerable adjustment to changeover from one part to another. Rapid software changeover is being facilitated by the use of a real-time, object-oriented software environment, modular software, graphical simulations for off-line software development, and an innovative dual VMEbus controller architecture. These agile features permit new products to be introduced with minimal downtime and system reconfiguration.

An impediment to the widespread use of formal methods for software development is the difficulty in dealing with specifications, namely using them consistently in the software process. One approach to easing the management of specifications and improving their impact in the software process is animation, allowing developers to “execute” formal specifications as prototypes. This paper illustrates how Prolog can serve a multifaceted role for animating and prototyping specifications—as a target language, as the compilation/translation language, and to facilitate the advantages of formal methods through help in building formal proofs of properties such as correctness. Further, there is an implicit claim that, because of the correctness and directness of the translation, a subset of Z, not definitively established here, can be viewed as equivalent to a subset of Prolog.

A generalized scheduling development environment allows a person who composes schedules to specify both an application and a methodology, in developing a scheduling program. The authors have designed such a system and have built a proof-of-concept prototype. The prototype has been tested on two fairly different application examples. It demonstrates the expressive capability of logic programming in representing the diversity of the two examples, and it exemplifies a method of achieving generality in the domain of scheduling.>

Ordinal reasoning plays a major role in human cognition. This paper identifies an important class of classification problems of patterns taken from ordinal domains and presents efficient, incremental algorithms for learning the classification rules from examples. We show that by adopting a monotonicity assumption of the output with respect to the input, inconsistencies among examples can be easily detected and the number of possible classification rules substantially reduced. By adopting a conservative classification criterion, the required number of rules further decreases. The monotonicity and conservatism of the classification also enable the resolution of conflicts among inconsistent examples and the graceful handling of don't knows and don't cares during the learning and classification phases. Two typical examples in which the suggested classification model works well are given. The first example is taken from the financial domain and the second from machining.

We describe a shell for expert systems written in Prolog. The shell provides a consultation environment and a range of explanation capabilities. The design of the shell is modular, making it very easy to extend the shell with extra features required by a particular expert system. The novelty of the shell is twofold. Firstly, it has a uniform design consisting of an integrated collection of meta‐interpreters. Secondly, there is a new approach for explaining ‘why not,’ when a query to the system fails.