Creative computing is an approach to computing education which emphasises the creation of interactive audiovisual software and an art-school influenced pedagogy. Given this emphasis on Dewey's "learning by doing", we set out to investigate the processes students use to develop their programs. We refer to these processes as the students' 'coding behaviour', and we expect that understanding it will provide us with valuable information about how students learn in our creative computing classes. As existing metrics were not sufficient, we introduce a new set of quantitative metrics to describe coding behaviours. The metrics consider factors such as students' vocabulary use and development, how fast and how much they alter the functionality of code over time and how they iterate on their code through text insert and delete operations. Many of our lessons involve providing students with demonstrator code which they use as a base for the development of their programs, so we use demo code as an entry point to our dataset. We look at programs students have written through developing the demo code in a dataset of over 16,000 programs. We clustered the demo code using the set of descriptive metrics. This lead to a set of clusters containing programs which are associated with distinct coding behaviours. Four was the ideal number of clusters for cluster density and separation. We found that the clusters had distinct behaviour patterns, that they were associated with different instructors and that they contained demo programs with different lengths.

Collaboration is built on trust, and establishing trust with a creative Artificial Intelligence is difficult when the decision process or internal state driving its behaviour isn't exposed. When human musicians improvise together, a number of extra-musical cues are used to augment musical communication and expose mental or emotional states which affect musical decisions and the effectiveness of the collaboration. We developed a collaborative improvising AI drummer that communicates its confidence through an emoticon-based visualisation. The AI was trained on musical performance data, as well as real-time skin conductance, of musicians improvising with professional drummers, exposing both musical and extra-musical cues to inform its generative process. Uni- and bi-directional extra-musical communication with real and false values were tested by experienced improvising musicians. Each condition was evaluated using the FSS-2 questionnaire, as a proxy for musical engagement. The results show a positive correlation between extra-musical communication of machine internal state and human musical engagement.

For the last decade, there has been growing interest in the STEAM approach (essentially combining methods and practices in arts, humanities and social sciences into STEM teaching and research) to develop better research and education, and enable us to produce students who can work most effectively in the current and developing market-place. However, despite this interest, there seems to be little quantitative evidence of the true power of STEAM learning, especially describing how it compares and performs with respect to more established approaches. To address this, we present a comparative, quantitative study of two distinct approaches to teaching programming, one based on STEAM (with an open-ended inquiry-based approach), the other based on a more traditional, non-STEAM approach (where constrained problems are set and solved). Our key results evidence how students exhibit different styles of programming in different types of lessons and, crucially, that students who tend to exhibit more of the style of programming observed in our STEAM lessons also tend to achieve higher grades. We present our claims through a range of visualisations and statistical validations which clearly show the significance of the results, despite the small scale of the study. We believe that this work provides clear evidence for the advantages of STEAM over non-STEAM, and provides a strong theoretical and technological framework for future, larger studies.

This article presents Gesture Interaction DEsigner (GIDE), an innovative application for gesture recognition. Instead of recognizing gestures only after they have been entirely completed, as happens in classic gesture recognition systems, GIDE exploits the full potential of gestural interaction by tracking gestures continuously and synchronously, allowing users to both control the target application moment to moment and also receive immediate and synchronous feedback about system recognition states. By this means, they quickly learn how to interact with the system in order to develop better performances. Furthermore, rather than learning the predefined gestures of others, GIDE allows users to design their own gestures, making interaction more natural and also allowing the applications to be tailored by users' specific needs. We describe our system that demonstrates these new qualities—that combine to provide fluid gesture interaction design—through evaluations with a range of performers and artists.

Loop pedals are real-time samplers that playback audio played previously by a musician. Such pedals are routinely used for music practice or outdoor "busking". However, loop pedals always playback the same material, which can make performances monotonous and boring both to the musician and the audience, preventing their widespread uptake in professional concerts. In response, we propose a new approach to loop pedals that addresses this issue, which is based on an analytical multi-modal representation of the audio input. Instead of simply playing back prerecorded audio, our system enables real-time generation of an audio accompaniment reacting to what is currently being performed by the musician. By combining different modes of performance - e.g. bass line, chords, solo - from the musician and system automatically, solo musicians can perform duets or trios with themselves, without engendering the so-called canned (boringly repetitive and unresponsive) music effect of loop pedals. We describe the technology, based on supervised classification and concatenative synthesis, and then illustrate our approach on solo performances of jazz standards by guitar. We claim this approach opens up new avenues for concert performance.

This paper proposes the notion of experience to help situate agents in their environment, providing a link on how the continually evolving environment impacts the evolution of an agent's BDI model and vice versa. Then, using the notion of shared experience as a primitive construct, we develop a novel formal model of shared intention which we believe more adequately describes social behaviour than traditional BDI logics that focus on individual agents. Whilst many philosophers have argued that collective intentionality cannot always be equated to the collection of the individual agents' intentions, there has been no AI model that addresses this issue. We believe this is the first attempt to develop an explicit notion of shared experience from an AI perspective.

Just as conventional institutions are organisational structures for coordinating the activities of multiple interacting individuals, electronic institutions provide a computational analogue for coordinating the activities of multiple interacting software agents. In this paper, we argue that open multi-agent systems can be effectively designed and implemented as electronic institutions, for which we provide a comprehensive computational model. More specifically, the paper provides an operational semantics for electronic institutions, specifying the essential data structures, the state representation and the key operations necessary to implement them. We specify the agent workflow structure that is the core component of such electronic institutions and particular instantiations of knowledge representation languages that support the institutional model. In so doing, we provide the first formal account of the electronic institution concept in a rigorous and unambiguous way.

This paper presents an extensive analysis of a sample of a social network of musicians. The network sample is first analyzed using standard complex network techniques to verify that it has similar properties to other web-derived complex networks. Content-based pairwise dissimilarity values between the musical data associated with the network sample are computed, and the relationship between those content-based distances and distances from network theory explored. Following this exploration, hybrid graphs and distance measures are constructed, and used to examine the community structure of the artist network. Finally, results of these investigations are shown to be mostly orthogonal between these distance spaces. These results are considered with a focus recommendation and discovery applications employing these hybrid measures as their basis.

Abstract In the original failure-divergence semantic model for Communicating Sequential Processes (CSP), the incomplete treatment of successful process termination, and in particular parallel termination, permitted unnatural processes to be defined. In response to these problems, a number of different solutions have been proposed by various authors since the original failure-divergence model was developed by Hoare, Brookes and Roscoe. This paper presents an alternative solution to this problem, which is both closer to the original semantic model and provides greater flexibility over the type of parallel termination semantics available in CSP.

The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding collaborations between the agent and bioinformatics communities to develop a different (agent-based) approach of computational frameworks both for data analysis and management in bioinformatics and for systems modelling and simulation in computational and systems biology. The collaborations gave rise to applications and integrated tools that we summarize and discuss in context of the state of the art in this area. We investigate on future challenges and argue that the field should still be explored from many perspectives ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages to be used by information agents, and to the adoption of agents for computational grids.

The use of agents of many different kinds in a variety of fields of computer science and artificial intelligence is increasing rapidly and is due, in part, to their wide applicability. The richness of the agent metaphor that leads to many different uses of the term is, however, both a strength and a weakness: its strength lies in the fact that it can be applied in very many different ways in many situations for different purposes; the weakness is that the term agent is now used so frequently that there is no commonly accepted notion of what it is that constitutes an agent. This paper addresses this issue by applying formal methods to provide a defining framework for agent systems. The Z specification language is used to provide an accessible and unified formal account of agent systems, allowing us to escape from the terminological chaos that surrounds agents. In particular, the framework precisely and unambiguously provides meanings for common concepts and terms, enables alternative models of particular classes of system to be described within it, and provides a foundation for subsequent development of increasingly more refined concepts.

Perhaps the most successful agent architectures, and certainly the best known, are those based on the Belief-Desire-Intention (BDI) framework. Despite the wealth of research that has accumulated on both formal and practical aspects of this framework, however, there remains a gap between the formal models and the implemented systems. In this paper, we build on earlier work by Rao aimed at narrowing this gap, by developing a strongly-typed, formal, yet computational model of the BDI-based AgentSpeak(L) language. AgentSpeak(L) is a programming language, based on the Procedural Reasoning System (PRS) and the Distributed Multi-Agent Reasoning System (dMARS), which determines the behaviour of the agents it implements. In developing the model, we add to Rao's work, identify some omissions, and progress beyond the description of a particular language by giving a formal specification of a general BDI architecture that can be used as the basis for providing further formal specifications of more sophisticated systems.

Previous work has addressed the development of a framework to categorise and understand agent-based systems. It described and formalised an agent-hierarchy that included objects, agents and autonomous agents, each with different levels of functionality, and provided a precise vocabulary with which to discuss agent systems. This paper reviews a large variety of further work that has built on that foundation in several ways. First, the framework itself has been refined to detail important aspects of agent functionality such as goal generation and adoption. Second, the structures and relationships between agents have been specified and analysed allowing a more complete understanding of the dynamics of agent systems. Third, existing systems and theories have been formalised within the framework so that they may be evaluated and compared in a coherent and consistent way. Finally, some steps have been taken in attempting to construct a methodology for the development of agent-based systems. Though this work spans a large range of concerns, it is based on a single set of basic concepts providing fundamental structure.

The specification, design and implementation of a text-based multiway interactive conferencing program are presented. The system is described in three parts: the user interface, the distribution mechanism for users' contributions, and the floor control scheme. One specific system of floor control using the formal specification language Z is specified. The separation of the distributed operation of the exchange of speech in the conference from the floor control mechanism has led to the possibility of implementing an open floor conferencing system, and then adding floor control. The only operations necessary to add floor control are those required to allow or prevent use of a channel from each user to any other. The extra state incurred in the conference server processes is the 2-D matrix of user by user channels, with each entry showing allowed/disallowed.>