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  • 1.
    Bhatt, Mehul
    et al.
    Örebro University, School of Science and Technology. Human-Centred Cognitive Assistance Lab. (HCC), University of Bremen, Bremen, Germany.
    Cutting, James
    Cornell University, Ithaca, USA.
    Levin, Daniel
    Department of Psychology and Human Development, Vanderbilt University, Nashville, USA.
    Lewis, Clayton
    University of Colorado, Boulder, USA.
    Cognition, Interaction, Design: Discussions as Part of the Codesign Roundtable 20172017In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 31, no 4, p. 363-371Article in journal (Refereed)
    Abstract [en]

    This transcript documents select parts of discus-sions on the confluence of cognition, interaction, design, and human behaviour studies. The interview and related events were held as part of the CoDesign 2017 Roundtable (Bhatt in CoDesign 2017—The Bremen Summer of Cognition and Design/CoDesign Roundtable. University of Bremen, Bremen, 2017) at the University of Bremen (Germany) in June 2017. The Q/A sessions were moderated by Mehul Bhatt (University of Bremen, Germany., and Örebro Uni-versity, Sweden) and Daniel Levin (Vanderbilt University, USA). Daniel Levin served in a dual role: as co-moderator of the discussion, as well as interviewee. The transcript is published as part of a KI Journal special issue on “Seman-tic Interpretation of Multi-Modal Human Behaviour Data” (Bhatt and Kersting in Special Issue on: Semantic Interpre-tation of Multimodal Human Behaviour Data, Artif Intell, 2017).

  • 2.
    Bhatt, Mehul
    et al.
    Örebro University, School of Science and Technology. Human-Centred Cognitive Assistance Lab. (HCC), University of Bremen, Bremen, Germany.
    Kersting, Kristian
    Technical University of Dortmund (DE), Dortmund, Germany.
    Semantic Interpretation of Multi-Modal Human-Behaviour Data: Making Sense of Events, Activities, Processes2017In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 31, no 4, p. 317-320Article in journal (Refereed)
    Abstract [en]

    This special issue presents interdisciplinary research—at the interface of artificial intelligence, cogni-tive science, and human-computer interaction—focussing on the semantic interpretation of human behaviour. The special issue constitutes an attempt to highlight and steer founda-tional methods research in artificial intelligence, in particular knowledge representation and reasoning, for the develop-ment of human-centred cognitive assistive technologies. Of specific interest and focus have been application outlets for basic research in knowledge representation and reason-ing and computer vision for the cognitive, behavioural, and social sciences.

  • 3.
    Cirillo, Marcello
    Örebro University, School of Science and Technology.
    Planning in inhabited environments: human-aware task planning and activity recognition2011In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 25, no 4, p. 355-358Article in journal (Refereed)
    Abstract [en]

    Our work addresses issues related to the cohabitation of service robots and people in unstructured environments. We propose new planning techniques to empower robot means-end reasoning with the capability of taking into account human intentions and preferences. We also address the problem of human activity recognition in instrumented environments. We employ a constraint-based approach to realize a continuous inference process to attach a meaning to sensor traces as detected by sensors distributed in the environment.

  • 4.
    Coradeschi, Silvia
    et al.
    Örebro University, School of Science and Technology.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Wrede, Britta
    Bielefeld University, Bielefeld, Germany.
    A short review of symbol grounding in robotic and intelligent systems2013In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 27, no 2, p. 129-136Article in journal (Refereed)
    Abstract [en]

    This paper gives an overview of the research papers published in Symbol Grounding in the period from the beginning of the 21st century up 2012. The focus is in the use of symbol grounding for robotics and intelligent system. The review covers a number of subtopics, that include, physical symbol grounding, social symbol grounding, symbol grounding for vision systems, anchoring in robotic systems, and learning symbol grounding in software systems and robotics. This review is published in conjunction with a special issue on Symbol Grounding in the Künstliche Intelligenz Journal.

  • 5.
    d. C. Silva-Lopez, Lia Susana
    et al.
    Örebro University, School of Science and Technology.
    Broxvall, Mathias
    Örebro University, School of Science and Technology.
    Loutfi, Amy
    Örebro University, School of Science and Technology.
    Karlsson, Lars
    Örebro University, School of Science and Technology.
    Towards configuration planning with partially ordered preferences: representation and results2015In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 9, no 2, p. 173-183Article in journal (Refereed)
    Abstract [en]

    Configuration planning for a distributed robotic system is the problem of how to configure the system over time in order to achieve some causal and/or information goals. A configuration plan specifies what components (sensor, actuator and computational devices), should be active at different times and how they should exchange information. However, not all plans that solve a given problem need to be equally good, and for that purpose it may be important to take preferences into account. In this paper we present an algorithm for configuration planning that incorporates general partially ordered preferences. The planner supports multiple preference categories, and hence it solves a multiple-objective optimization problem: for a given problem, it finds all possible valid, non-dominated configuration plans. The planner has been able to successfully cope with partial ordering relations between quantitative preferences in practically acceptable times, as shown in the empirical results. Preferences here are represented as c-semirings, and are used for establishing dominance of a solution over another in order to obtain a set of configuration plans that will constitute the solution of a configuration planning problem with partially ordered preferences. The dominance operators tested in this paper are Pareto and Lorenz dominance. Our solver considers one guiding heuristic for obtaining the first solution, and then switches to a dominance based monotonically decreasing heuristic used for pruning dominated partial configuration plans. In our empirical results, we perform a statistical study in the space of problem instances and establish families of problems for which our approach is computationally feasible.

  • 6.
    Daoutis, Marios
    Örebro University, School of Science and Technology.
    Knowledge based perceptual anchoring: grounding percepts to concepts in cognitive robots2013In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, p. 1-4Article in journal (Refereed)
    Abstract [en]

    Perceptual anchoring is the process of creating and maintaining a connection between the sensor data corresponding to a physical object and its symbolic description. It is a subset of the symbol grounding problem, introduced by Harnad (Phys. D, Nonlinear Phenom. 42(1–3):335–346, 1990) and investigated over the past years in several disciplines including robotics. This PhD dissertation focuses on a method for grounding sensor data of physical objects to the corresponding semantic descriptions, in the context of cognitive robots where the challenge is to establish the connection between percepts and concepts referring to objects, their relations and properties. We examine how knowledge representation can be used together with an anchoring framework, so as to complement the meaning of percepts while supporting better linguistic interaction with the use of the corresponding concepts. The proposed method addresses the need to represent and process both perceptual and semantic knowledge, often expressed in different abstraction levels, while originating from different modalities. We then focus on the integration of anchoring with a large scale knowledge base system and with perceptual routines. This integration is applied in a number of studies, where in the context of a smart home, several evaluations spanning from spatial and commonsense reasoning to linguistic interaction and concept acquisition.

  • 7.
    Hertzberg, Joachim
    et al.
    Osnabrück University, Osnabrück, Germany .
    Zhang, Jianwei
    Hamburg University, Hamburg, Germany .
    Zhang, Liwei
    Hamburg University, Hamburg, Germany .
    Rockel, Sebastian
    Hamburg University, Hamburg, Germany .
    Neumann, Bernd
    Hamburg University, Hamburg, Germany .
    Lehmann, Jos
    Hamburg University, Hamburg, Germany .
    Dubba, Krishna S.R.
    University of Leeds, Leeds, England .
    Cohn, Anthony G.
    University of Leeds, Leeds, England .
    Saffiotti, Alessandro
    Örebro University, School of Science and Technology.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Mansouri, Masoumeh
    Örebro University, School of Science and Technology.
    Konečný, Štefan
    Örebro University, School of Science and Technology.
    Günther, Martin
    Osnabrück University, Osnabrück, Germany .
    Stock, Sebastian
    Osnabrück University, Osnabrück, Germany .
    Seabra Lopes, Luis
    University of Aveiro, Aveiro, Portugal .
    Oliveira, Miguel
    University of Aveiro, Aveiro, Portugal .
    Lim, Gi Hyun
    University of Aveiro, Aveiro, Portugal .
    Kasaei, Hamidreza
    University of Aveiro, Aveiro, Portugal .
    Mokhtari, Vahid
    University of Aveiro, Aveiro, Portugal .
    Hotz, Lothar
    HITeC Hamburger Informatik Technologie-Center e. V., Hamburg, Germany .
    Bohlken, Wilfried
    HITeC Hamburger Informatik Technologie-Center e. V., Hamburg, Germany .
    The RACE Project: Robustness by Autonomous Competence Enhancement2014In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 28, no 4, p. 297-304Article in journal (Refereed)
    Abstract [en]

    This paper reports on the aims, the approach, and the results of the European project RACE. The project aim was to enhance the behavior of an autonomous robot by having the robot learn from conceptualized experiences of previous performance, based on initial models of the domain and its own actions in it. This paper introduces the general system architecture; it then sketches some results in detail regarding hybrid reasoning and planning used in RACE, and instances of learning from the experiences of real robot task execution. Enhancement of robot competence is operationalized in terms of performance quality and description length of the robot instructions, and such enhancement is shown to result from the RACE system.

  • 8.
    Junges, Robert
    et al.
    Örebro University, School of Science and Technology.
    Klügl, Franziska
    Örebro University, School of Science and Technology.
    Learning Tools for Agent-based Modeling and Simulation2013In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 27, no 3, p. 273-280Article in journal (Refereed)
    Abstract [en]

    In this project report, we describe ongoing research on supporting the development of agent-based simulation models. The vision is that the agents themselves should learn their (individual) behavior model, instead of letting a human modeler test which of the many possible agent-level behaviors leads to the correct macro-level observations. To that aim, we integrate a suite of agent learning tools into SeSAm, a fully visual platform for agent-based simulation models. This integration is the focus of this contribution.

  • 9.
    Kristoffersson, Annica
    Örebro University, School of Science and Technology.
    Using Presence, Spatial Formations and Sociometry to Measure Interaction Quality in Mobile Robotic Telepresence Systems2014In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, ISSN 0933-1875, Vol. 28, no 1, p. 49-52Article in journal (Refereed)
    Abstract [en]

    The use of video mediated communication technologies for interacting is increasing. An extension of these is mobile robotic telepresence (MRP) systems, video conferencing systems mounted on teleoperated mobile robots. The nature of the interaction via an MRP system is more complex than face-to-face interaction and involves not only social communication but also mobility. This research focuses on the use of MRP systems in domestic settings in elder care and contributes to the understanding of how interaction is affected by MRP system embodiment.

  • 10.
    Pecora, Federico
    Örebro University, School of Science and Technology.
    Is Model-Based Robot Programming a Mirage?: A Brief Survey of AI Reasoning in Robotics2014In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 28, no 4, p. 255-261Article in journal (Refereed)
    Abstract [en]

    Researchers in AI and Robotics have in common the desire to “make robots intelligent”, evidence of which can be traced back to the earliest AI systems. One major contribution of AI to Robotics is the model-centered approach, whereby intelligence is the result of reasoning in models of the world which can be changed to suit different environments, physical capabilities, and tasks. Dually, robots have contributed to the formulation and resolution of challenging issues in AI, and are constantly eroding the modeling abstractions underlying AI problem solving techniques. Forty-eight years after the first AI-driven robot, this article provides an updated perspective on the successes and challenges which lie at the intersection of AI and Robotics.

  • 11.
    Trincavelli, Marco
    Örebro University, School of Science and Technology.
    Gas discrimination for mobile robots2011In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 25, no 4, p. 351-354Article in journal (Refereed)
    Abstract [en]

    Robots with gas sensing capabilities can address tasks like monitoring of polluted areas, detection of gas leaks, exploration of hazardous zones or search for explosives. Most of the currently available gas sensing technologies suffer from a number of shortcomings like lack of selectivity (the sensor responds to more than one chemical compound), slow response, drift in the response, and cross-sensitivity to physical variables like temperature and humidity. The main topic of this dissertation is the discrimination of gases, therefore the scarce selectivity and slow response are the limitations of direct concern. One of the possible solutions to overcome the poor selectivity of a single sensor is to use an array of gas sensors and to interpret the response of the whole array using signal processing techniques and pattern recognition algorithms. This is an established technology as long as the sensors are placed in a measuring chamber. However, discrimination of gases with a mobile robot presents additional challenges because the sensors are directly exposed to the highly dynamic environment to be analyzed. Given the slow dynamics of the sensors, the steady-state of the response is never achieved and therefore the discrimination has to be performed on the transient phase. The contributions presented in the summarized thesis focus around the design of algorithms for gas identification in the transient phase, thus they are particularly suited to mobile robotics applications.

1 - 11 of 11
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