We present a general logical framework for reasoning about agents’ cognitive attitudes of both epistemic type and motivational type. We show that it allows us to express a variety of relevant concepts for qualitative decision theory including the concepts of knowledge, belief, strong belief, conditional belief, desire, conditional desire, strong desire, and preference. We also present two extensions of the logic, one by the notion of choice and the other by dynamic operators for belief change and desire change, and we apply the former to the analysis of single-stage games under incomplete information. We provide sound and complete axiomatizations for the basic logic and for its two extensions.

Argumentation and eXplainable Artificial Intelligence (XAI) are closely related, as in the recent years, Argumentation has been used for providing Explainability to AI. Argumentation can show step by step how an AI System reaches a decision; it can provide reasoning over uncertainty and can find solutions when conflicting information is faced. In this survey, we elaborate over the topics of Argumentation and XAI combined, by reviewing all the important methods and studies, as well as implementations that use Argumentation to provide Explainability in AI. More specifically, we show how Argumentation can enable Explainability for solving various types of problems in decision-making, justification of an opinion, and dialogues. Subsequently, we elaborate on how Argumentation can help in constructing explainable systems in various applications domains, such as in Medical Informatics, Law, the Semantic Web, Security, Robotics, and some general purpose systems. Finally, we present approaches that combine Machine Learning and Argumentation Theory, toward more interpretable predictive models.

We revisit an old topic in algorithms, the deterministic walk on a finite graph which always moves toward the nearest unvisited vertex until every vertex is visited. There is an elementary connection between this cover time and ball-covering (metric entropy) measures. For some familiar models of random graphs, this connection allows the order of magnitude of the cover time to be deduced from first passage percolation estimates. Establishing sharper results seems a challenging problem.

This paper explores versions of the Yoneda Lemma in settings founded upon FM sets. In particular, we explore the lemma for three base categories: the category of nominal sets and equivariant functions; the category of nominal sets and all finitely supported functions, introduced in this paper; and the category of FM sets and finitely supported functions. We make this exploration in ordinary, enriched and internal settings. We also show that the finite support of Yoneda natural transformations is a theorem for free.

Parallel reduction is a major component of parallel programming and widely used for summarisation and aggregation. It is not well understood, however, what sorts of non-trivial summarisations can be implemented as parallel reductions. This paper develops a calculus named λAS, a simply typed lambda calculus with algebraic simplification. This calculus provides a foundation for studying a parallelisation of complex reductions by equational reasoning. Its key feature is δ abstraction. A δ abstraction is observationally equivalent to the standard λ abstraction, but its body is simplified before the arrival of its arguments using algebraic properties such as associativity and commutativity. In addition, the type system of λAS guarantees that simplifications due to δ abstractions do not lead to serious overheads. The usefulness of λAS is demonstrated on examples of developing complex parallel reductions, including those containing more than one reduction operator, loops with conditional jumps, prefix sum patterns and even tree manipulations.

In general, the clustering problem is NP-hard, and global optimality cannot be established for non-trivial instances. For high-dimensional data, distance-based methods for clustering or classification face an additional difficulty, the unreliability of distances in very high-dimensional spaces. We propose a probabilistic, distance-based, iterative method for clustering data in very high-dimensional space, using the ℓ1-metric that is less sensitive to high dimensionality than the Euclidean distance. For K clusters in ℝn, the problem decomposes to K problems coupled by probabilities, and an iteration reduces to finding Kn weighted medians of points on a line. The complexity of the algorithm is linear in the dimension of the data space, and its performance was observed to improve significantly as the dimension increases.

Electronic systems designed to improvise with a live instrumental performer are a constant mediation of musical language and artificial decision-making. Often these systems are designed to elicit a reaction in a very broad way, relying on segmenting and playing back audio material according to a fixed or mobile set of rules or analysis. As a result, such systems can produce an outcome that sounds generic across different improvisers, or restrict meaningful electroacoustic improvisation to those performers with a matching capacity for designing improvisatory electroacoustic processing. This article documents the development of an improvisatory electroacoustic instrument for pianist Maria Donohue as a collaborative process for music-making. The Donohue+ program is a bespoke electroacoustic improvisatory system designed to augment the performance capabilities of Maria, enabling her to achieve new possibilities in live performance. Through the process of development, Maria’s performative style, within the broader context of free improvisation, was analysed and used to design an interactive electronic system. The end result of this process is a meaningful augmentation of the piano in accordance with Maria’s creative practice, differing significantly from other improvising electroacoustic instruments she has previously experimented with. Through the process of development, Donohue+ identifies a practice for instrument design that engages not only with a performer’s musical materials but also with a broader free improvisation aesthetic.

This paper describes the background and motivations behind the author’s electroacoustic game-pieces Pathfinder (2016) and ICARUS (2019), designed specifically for his performance practice with an augmented drum kit. The use of game structures in music is outlined, while musical expression in the context of commercial musical games using conventional game controllers is discussed. Notions such as agility, agency and authorship in music composition and improvisation are in parallel with game design and play, where players are asked to develop skills through affordances within a digital game-space. It is argued that the recent democratisation of game engines opens a wide range of expressive opportunities for real-time game-based improvisation and performance. Some of the design decisions and performance strategies for the two instrument-controlled games are presented to illustrate the discussion; this is done in terms of game design, physical control through the augmented instrument, live electronics and overall artistic goals of the pieces. Finally, future directions for instrument-controlled electroacoustic game-pieces are suggested.

This article describes my own way to improvise with space using a computer-based tool implemented in SuperCollider. The objective of this spatial performance tool is to have an ergonomic spatio-temporal and spectral control over numerous sound objects in real time, in order to alternate between spatialised polyrhythms and textures. After a brief review of spatial audio context, the spatial performance tool is summarised and detailed here by focusing on one of the core parameters: the playback speeds, which can act both on rhythm and space and enable among others the spatio-temporal articulation of the performance. As well as discussing the word ‘comprovisation’ and my conception of human–computer improvisation, the possibilities and approach of the tool in terms of improvisation and controllerism are illustrated through the use and combination of different controllers (computer keyboard, tactile interfaces, force touch sensors). Whereas some controllers are more dedicated to the selection and triggering of streams of spatialised sound events, others have their own mappings and ways of acting on some parameters (depending on the temporality of the sounds: playing or future events).