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AI Communications is a journal on Artificial Intelligence (AI) which has a close relationship to ECCAI (the European Coordinating Committee for Artificial Intelligence). It covers the whole AI community: scientific institutions as well as commercial and industrial companies.
AI Communications aims to enhance contacts and information exchange between AI researchers and developers, and to provide supranational information to those concerned with AI and advanced information processing. AI Communications publishes refereed articles concerning scientific and technical AI procedures, provided they are of sufficient interest to a large readership of both scientific and practical background. In addition it contains high-level background material, both at the technical level as well as the level of opinions, policies and news. The Editorial and Advisory Board is appointed by the Editor-in-Chief.
Authors: Durães, Dalila | Toala, Rámon | Gonçalves, Filipe | Novais, Paulo
Article Type: Research Article
Abstract: Nowadays, society is in constant evolution, which allows constant production of new knowledge. In this way, citizens are constantly pressured to obtain new qualifications through training/requalification. The need for qualified people has been growing exponentially, which means that resources for education/training are limited to being used more efficiently. In this paper we will focus in the design the user model, so, we propose an innovative approach to design a user model that monitors the user’s biometric behaviour by measuring their level of attention during e-learning activities. In addition, a machine learning categorization model is presented that oversees user activity during …the session. We intend to use non-invasive methods of intelligent tutoring systems, observing the interaction of users during the session. Furthermore, this article highlights the main biometric behavioural variations for each activity and bases the set of attributes relevant to the development of machine learning classifiers to predict users’ learning preference. The results show that there are still mechanisms that can be explored and improved to better understand the complex relationship between human behaviour, attention and evaluation that could be used to implement better learning strategies. These results can be decisive in improving ITS in e-learning environments and to predict user behaviour based on their interaction with technology devices. Show more
Keywords: Intelligent tutoring systems, adaptive system, attention, biometric behaviour
DOI: 10.3233/AIC-190624
Citation: AI Communications, vol. 32, no. 3, pp. 161-174, 2019
Authors: Barták, Roman | Švancara, Jiří | Škopková, Věra | Nohejl, David | Krasičenko, Ivan
Article Type: Research Article
Abstract: The problem of Multi-Agent Path Finding (MAPF) is to find paths for a fixed set of agents from their current locations to some desired locations in such a way that the agents do not collide with each other. This problem has been extensively theoretically studied, frequently using an abstract model, that expects uniform durations of moving primitives and perfect synchronization of agents/robots. In this paper we study the question of how the abstract plans generated by existing MAPF algorithms perform in practice when executed on real robots, namely Ozobots. In particular, we use several abstract models of MAPF, including a …robust version and a version that assumes turning of a robot, we translate the abstract plans to sequences of motion primitives executable on Ozobots, and we empirically compare the quality of plan execution (real makespan, the number of collisions). Show more
Keywords: Path planning, multi-agent systems, real robots
DOI: 10.3233/AIC-190621
Citation: AI Communications, vol. 32, no. 3, pp. 175-189, 2019
Authors: Vignolo, Leandro D. | Albornoz, Enrique M. | Martínez, César E.
Article Type: Research Article
Abstract: Speaker state recognition is an important issue to understand the human behaviour and to achieve more comprehensive speech interactive systems, and therefore has received much attention in recent years. This work addresses the automatic classification of three types of child emotions in vocalisations: neutral mood, fussing (negative mood) and crying (negative mood). Speech, in a broad sense, contains a lot of para-linguistic information that can be revealed by means of different methods for feature extraction and, in this case, these would be useful for mood detection. Here, several set of features are proposed, combined and compared with state-of-art characteristics used …for speech-related tasks, and these are based on spectral information, bio-inspired ear model, auditory sparse representations with dictionaries, optimised wavelet coefficients and optimised filter bank for cepstral representation. All the experiments were performed using the Extreme Learning Machines as classifier because it is a state-of-art classifier and to achieve comparable results. The results show that by means of the proposed feature extraction methods it is possible to improve the performance provided by the baseline features. Also, different combinations of the developed feature sets were studied in order to further exploit their properties. Show more
Keywords: Mood classification, crying detection, sparse representations, filter bank optimisation, spectral features, bio-inspired ear model, wavelet packets
DOI: 10.3233/AIC-190620
Citation: AI Communications, vol. 32, no. 3, pp. 191-206, 2019
Authors: Anselma, Luca | Piovesan, Luca | Terenziani, Paolo
Article Type: Research Article
Abstract: Time is pervasive of the human way of approaching reality, so that it has been widely studied in many research areas, including AI and relational Temporal Databases (TDB). While temporally imprecise information has been widely studied by the AI community, only few approaches have faced temporal indeterminacy (in particular, “don’t know exactly when” indeterminacy) in TDBs. Indeed, as we will show in this paper, the treatment of time in general, and of temporal indeterminacy in particular, involves the introduction of implicit forms of data representation in TDBs. As a consequence, we propose a new AI -style methodology to …cope with temporal indeterminacy in TDBs. Specifically, we show that typical AI notions and techniques, such as making explicit the semantics of the representation formalism, and adopting symbolic manipulation techniques based on such a semantics, can be fruitfully exploited in the development of a “principled ” treatment of indeterminate time in relational databases. Show more
Keywords: Temporal data, data representation and semantics, query semantics, symbolic manipulation
DOI: 10.3233/AIC-190619
Citation: AI Communications, vol. 32, no. 3, pp. 207-221, 2019
Authors: de Garrido, Luis | Gómez Sanz, Jorge | Pavón, Juan
Article Type: Research Article
Abstract: Many creative methods, such as different types of brainstorming, are based on the collaboration among a set of persons. The collaboration follows some well established workflows, which could be formalized. This would allow the generation of computational models that can be implemented to make some tools that facilitate the enactment of creative processes, or the simulation for the analysis of their characteristics. This work shows how to model this kind of collaborative creative processes as multi-agent systems, by representing the participants as interacting agents in well-defined workflows. This is done with the INGENIAS modeling language and tools, which also support …rapid prototyping using the JADE agent platform. A concrete creative method, Symbolic Brainstorming, is used to illustrate and validate the feasibility of the approach. Show more
Keywords: Multi-agent systems (MAS), computational creativity, symbolic Brainstorming, agent-based modeling, JADE, INGENIAS
DOI: 10.3233/AIC-190618
Citation: AI Communications, vol. 32, no. 3, pp. 223-233, 2019
Authors: Szymański, Julian | Naruszewicz, Maciej
Article Type: Research Article
Abstract: The paper reviews methods on automatic annotation of texts with Wikipedia entries. The process, called Wikification aims at building references between concepts identified in the text and Wikipedia articles. Wikification finds many applications, especially in text representation, where it enables one to capture the semantic similarity of the documents. Also, it can be considered as automatic tagging of the text. We describe typical approaches to Wikification, and identify their advantages and disadvantages. The main problem for wide usage of the Wikification method is the lack of open-sourced frameworks that enable researchers to work cooperatively on that problem. Also problematic is …the lack of a unified platform for evaluation of the results proposed by different approaches. Show more
Keywords: Wikipedia, Wikification, name entity recognition, disambiguation, concepts identification
DOI: 10.3233/AIC-190581
Citation: AI Communications, vol. 32, no. 3, pp. 235-251, 2019
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