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  • 1.
    Abedin, Md Reaz Ashraful
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hellström, Thomas
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Self-supervised language grounding by active sensing combined with Internet acquired images and text2017In: Proceedings of the Fourth International Workshop on Recognition and Action for Scene Understanding (REACTS2017) / [ed] Jorge Dias George Azzopardi, Rebeca Marf, Málaga: REACTS , 2017, p. 71-83Conference paper (Refereed)
    Abstract [en]

    For natural and efficient verbal communication between a robot and humans, the robot should be able to learn names and appearances of new objects it encounters. In this paper we present a solution combining active sensing of images with text based and image based search on the Internet. The approach allows the robot to learn both object name and how to recognise similar objects in the future, all self-supervised without human assistance. One part of the solution is a novel iterative method to determine the object name using image classi- fication, acquisition of images from additional viewpoints, and Internet search. In this paper, the algorithmic part of the proposed solution is presented together with evaluations using manually acquired camera images, while Internet data was acquired through direct and reverse image search with Google, Bing, and Yandex. Classification with multi-classSVM and with five different features settings were evaluated. With five object classes, the best performing classifier used a combination of Pyramid of Histogram of Visual Words (PHOW) and Pyramid of Histogram of Oriented Gradient (PHOG) features, and reached a precision of 80% and a recall of 78%.

  • 2.
    Baranwal, Neha
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Singh, Avinash
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Extracting Primary Objects and Spatial Relations from Sentences2019Conference paper (Refereed)
    Abstract [en]

    In verbal human-robot interaction natural language utterances have to be grounded in visual scenes by the robot. Visual language grounding is a challenging task that includes identifying a primary object among several objects, together with the object properties and spatial relations among the objects. In this paper we focus on extracting this information from sentences only. We propose two language modelling techniques, one uses regular expressions and the other one utilizes Euclidian distance. We compare these two proposed techniques with two other techniques that utilize tree structures, namely an extended Hobb’s algorithm and an algorithm that utilizes a Stanford parse tree. A comparative analysis between all language modelling techniques shows that our proposed two approaches require less computational time than the tree-based approaches. All approaches perform good identifying the primary object and its property, but for spatial relation extraction the Stanford parse tree algorithm performs better than the other language modelling techniques. Time elapsed for the Stanford parse tree algorithm is higher than for the other techniques.

  • 3.
    Becerra-Bonache, Leonor
    et al.
    Universitat Rovira i Virgili.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Jimenez-Lopez, M. Dolores
    Universitat Rovira i Virgili.
    L systems as Bio-MAS for natural language processing2010In: Trends in practical applications of agents and multiagent systems: 8th International Conference on Practical Applications of Agents and Multiagent Systems (PAAMS 2010) / [ed] Y. Demazeau et al., Berlin: Springer , 2010, p. 395-402Conference paper (Refereed)
    Abstract [en]

    In this paper, we claim that Lindenmayer systems (L systems) –more precisely, ET0L systems– can be considered as bio-inspired multi-agent systems that, because of its inherent features, can be usefully applied to the field of natural language processing (NLP). L systems are a biologically inspired branch of the field of formal languages that provide a parallel and non-sequential grammatical formalism and that can be expressed as a multi-agent system. Taking into account these features and the benefits of the multi-agent approach to NLP, we propose to apply L systems to the description, analysis and processing of natural languages.

  • 4.
    Becerra-Bonache, Leonor
    et al.
    Universitat Rovira i Virgili.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Jimenez-Lopez, M. Dolores
    Universitat Rovira i Virgili.
    The linguistic relevance of Lindenmayer systems2010In: Proceedings of the international conference on agents and artificial intelligence:  volume 2 - Agents, Valencia, Spain - ICAART / [ed] J. Filipe, A. Fred, and B. Sharp, Valencia: INSTICC Press , 2010, p. 395-402Conference paper (Refereed)
    Abstract [en]

    In this paper, we investigate the linguistic relevance of Lindenmayer Systems (L Systems). L systems were introduced in the late sixties by Aristid Lindemayer as a mathematical theory of biological development. Thus they can be considered as one of the first bio-inspired models in the theory of formal languages. Two main properties in L systems are 1) the idea of parallelism in the rewriting process and 2) their expressiveness to describe non-context free structures that can be found in natural languages. Therefore, the linguistic relevance of this formalism is clearly based on three main features: bio-inspiration, parallelism and generation of non-context free languages. Despite these interesting properties, L systems have not been investigated from a linguistic point of view. With this paper we point out the interest of applying these bio-inspired systems to the description and processing of natural language.

  • 5.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Graph Transformation for Incremental Natural Language Analysis.2014Other (Other academic)
  • 6.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Mildly context-sensitive grammar formalisms and natural language2010In: Language as a Complex System: Interdisciplinary Approaches / [ed] Gemma Bel-Enguix and M. Dolores Jimenez-Lopez, Newcastle upon Tyne, UK: Cambridge Scholars Publishing , 2010, p. 71-91Chapter in book (Other (popular science, discussion, etc.))
  • 7.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Björklund, Henrik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Drewes, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Algorithmic properties of Millstream systems2010In: Developments in Language Theory: 14th International Conference, DLT 2010 / [ed] Sheng Yu, Springer Berlin/Heidelberg, 2010, p. 54-65Conference paper (Refereed)
    Abstract [en]

    Millstream systems have recently been proposed as a formalization of the linguistic idea that natural language should be described as a combination of different modules related by interfaces. In this paper we investigate algorithmic properties of Millstream systems having regular tree grammars as modules and MSO logic as interface logic. We focus on the so-called completion problem: Given trees generated by a subset of the modules, can they be completed into a valid configuration of the Millstream system?

  • 8.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Björklund, Johanna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Kutrib, Martin
    Institut fur Informatik, Universität Giessen.
    Deterministic Stack Transducers2016In: Implementation and Application of Automata / [ed] Yo-Sub Han and Kai Salomaa, Springer, 2016, p. 27-38Conference paper (Refereed)
    Abstract [en]

    We introduce and investigate stack transducers, which are one-way stack automata with an output tape. A one-way stack automaton is a classical pushdown automaton with the additional ability to move the stack head inside the stack without altering the contents. For stack transducers, we distinguish between a digging and a non-digging mode. In digging mode, the stack transducer can write on the output tape when its stack head is inside the stack, whereas in non-digging mode, the stack transducer is only allowed to emit symbols when its stack head is at the top of the stack. These stack transducers have a motivation from natural language interface applications, as they capture long-distance dependencies in syntactic, semantic, and discourse structures.We study the computational capacity for deterministic digging and non-digging stack transducers, as well as for their non-erasing and checking versions. We finally show that even for the strongest variant of stack transducers the stack languages are regular.

  • 9.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Björklund, Johanna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Kutrib, Martin
    Deterministic Stack Transducers2017In: International Journal of Foundations of Computer Science, ISSN 0129-0541, Vol. 28, no 5, p. 583-601Article in journal (Refereed)
    Abstract [en]

    We introduce and investigate stack transducers, which are one-way stack automata with an output tape. A one-way stack automaton is a classical pushdown automaton with the additional ability to move the stack head inside the stack without altering the contents. For stack transducers, we distinguish between a digging and a non-digging mode. In digging mode, the stack transducer can write on the output tape when its stack head is inside the stack, whereas in non-digging mode, the stack transducer is only allowed to emit symbols when its stack head is at the top of the stack. These stack transducers have a motivation from natural-language interface applications, as they capture long-distance dependencies in syntactic, semantic, and discourse structures. We study the computational capacity for deterministic digging and non-digging stack transducers, as well as for their non-erasing and checking versions. We finally show that even for the strongest variant of stack transducers the stack languages are regular.

  • 10.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Bordihn, Henning
    Information, codes and languages: Essays dedicated to Helmut Jürgensen on the occassion of his 75th birthday – Preface2018In: Journal of Automata, Languages and Combinatorics, ISSN 1430-189X, Vol. 23, no 1–3, p. 2p. 3-4Article in journal (Refereed)
    Abstract [en]

    This special issue is dedicated to Professor Helmut Jürgensen on the occasion of his 75th birthday and in appreciation of his scientific work and his impact as teacher, mentor, and person. The sixteen papers in this special issue were submitted by invitation of the guest editors. Each paper was reviewed by at least two referees. The authors of the papers in this special issue are collaborators, co-authors, or scientific descendents of Helmut Jürgensen.

  • 11.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Bordihn, Henning
    Institut für Informatik, Universität Potsdam.
    Holzer, Markus
    Institut für Informatik, Universität Giessen.
    Kutrib, Martin
    Institut für Informatik, Universität Giessen.
    On input-revolving deterministic and nondeterministic finite automata2009In: Information and Computation, ISSN 0890-5401, E-ISSN 1090-2651, Vol. 207, p. 1140-1155Article in journal (Refereed)
    Abstract [en]

    We introduce and investigate input-revolving finite automata, which are (nondeterministic) finite state automata with additional ability to shift the remaining part of the input. Three different modes of shifting are considered, namely revolving to the left, revolving to the right, and circular-interchanging. We investigate the computational capacities of these three types of automata and their deterministic variants, comparing any of the six classes of automata with each other and with further classes of well-known automata. In particular, it is shown that nondeterminism is better than determinism, that is, for all three modes of shifting there is a language accepted by the nondeterministic model but not accepted by any determinstic automaton of the same type. Concerning the closure properties most of the deterministic language families studied are not closed under standard operations. For example, we show that the family of languages accepted by deterministic right-revolving finite automata is an anti-AFL which is not closed under reversal and intersection.

  • 12.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Drewes, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Millstream Systems2009Report (Other academic)
    Abstract [en]

    We introduce Millstream systems, a mathematical framework in the tradition of the Theory of Computation that uses logic to formalize the interfaces between different aspects of language, the latter being described by any number of independent modules. Unlike other approaches that serve a similar goal, Millstream systems neither presuppose nor establish a particular linguistic theory or focus, but can be instantiated in various ways to accomodate different points of view.

  • 13.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Drewes, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Millstream Systems: a formal model for linking language modules by interfaces2010In: Proc. ACL 2010 Workshop on Applications of Tree Automata in Natural Language Processing (ATANLP 2010), The Association for Computer Linguistics , 2010Conference paper (Refereed)
  • 14.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Drewes, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hellström, Thomas
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Grammatical Inference of Graph Transformation Rules2015In: Proceedings of the 7th Workshop on Non-Classical Modelsof Automata and Applications (NCMA 2015), Austrian Computer Society , 2015, p. 73-90Conference paper (Refereed)
  • 15.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Drewes, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Jürgensen, Helmut
    Department of Computer Science, The University of Western Ontario, London, Canada.
    van der Merwe, Brink
    Department of Computer Science, Stellenbosch University, South Africa.
    Correct readers for the incremental construction of Millstream configurations by graph transformation2012Report (Other academic)
    Abstract [en]

    Millstream systems have been proposed as a non-hierarchical method for modelling natural language. Millstream congurations represent and connect multiple structural aspects of sentences. We present a method by which the Millstream congurations corresponding to a sentence are constructed. The construction is incremental, that is, it proceeds as the sentence is being read and is complete when the end of the sentence is reached. It is based on graph transformations and a lexicon which associates words with rules for the graph transformations.

  • 16.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Drewes, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Jürgensen, Helmut
    The University of Western Ontario.
    van der Merwe, Brink
    University of Stellenbosch.
    Correct Readers for the Incremental Construction of Millstream Configurations by Graph TransformationManuscript (preprint) (Other academic)
  • 17.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Drewes, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Jürgensen, Helmut
    Department of Computer Science, Western University, London, Canada.
    van der Merwe, Brink
    Department of Computer Science, Stellenbosch University, South Africa.
    Graph transformation for incremental natural language analysis2014In: Theoretical Computer Science, ISSN 0304-3975, E-ISSN 1879-2294, Vol. 531, p. 1-25Article in journal (Refereed)
    Abstract [en]

    Millstream systems have been proposed as a non-hierarchical method for modelling natural language. Millstream configurations represent and connect multiple structural aspects of sentences. We present a method by which the Millstream configurations corresponding to a sentence are constructed. The construction is incremental, that is, it proceeds as the sentence is being read and is complete when the end of the sentence is reached. It is based on graph transformations and a lexicon which associates words with graph transformation rules that implement the incremental construction process.

  • 18.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Drewes, Frank
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Jürgensen, Helmut
    Middlesex College, The University of Western Ontario.
    van der Merwe, Brink
    Department of Mathematical Sciences, University of Stellenbosch.
    Incremental Construction of Millstream Configurations Using Graph Transformation2011In: Proceedings of the 9th International Workshop on Finite State Methods and Natural Language Processing, Stroudsburg: Association for Computational Linguistics , 2011, p. 93-97Conference paper (Refereed)
  • 19.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Ewert, Sigrid
    University of the Witwatersrand, Johannesburg, South Africa.
    Describing resource allocation to dynamically formed groups with grammars2019In: Simulation and modeling methodologies, technologies and applications: 7th international conference, (SIMULTECH) 2017, Madrid, Spain, July 26-28, 2017 : revised selected papers / [ed] Mohammad S. Obaidat, Tuncer I. Ören and Floriano De Rango, Springer, 2019, , p. 23p. 153-176Chapter in book (Refereed)
    Abstract [en]

    In this paper we model dynamic group formation and resource allocation with grammars in order to gain a deeper understanding into the involved processes. Modelling with grammars allows us to describe resource allocation and group formation as generative processes that provide, at any given time, information about at what stage the process of group formation and resource allocation is. We divide our model into four phases: (1) resource supply, (2) candidate group formation, (3) final group formation, and (4) resource distribution. In particular, we show that we can use permitting random context grammars to describe the first two phases. For the third phase we introduce an algorithm that determines based on a resource allocation strategy the final group to which resources are distributed. The last phase is described with random context grammars under a specific leftmost derivation mode. Our model shows that if information about the available resource and candidate group formation is distributed and kept separate, then the synchronisation of this information at a later stage (i.e. resource distribution phase) needs a more powerful grammar model.

  • 20.
    Bensch, Suna
    et al.
    Umeå University. Department of Computing Science.
    Ewert, Sigrid
    Raborife, Mpho
    Modelling the Formation of Virtual Buying Cooperatives with Grammars of Regulated Rewriting2017In: Proceedings of the 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, SciTePress, 2017, p. 45-55Conference paper (Refereed)
    Abstract [en]

    In this paper we model virtual buying cooperatives (VBC) with grammars of regulated rewriting and show that, if VBC relevant information is distributed over several successive VBC processes and must, in a later stage, be synchronised and co-ordinated, the formal grammar needs to be very powerful with respect to mode of derivation and thus generative capacity. In particular, we show how to model the supplier phase, invitation phase, and declaration phase of a VBC with random permitting context grammars and the VBC reservation phase with random context grammars under a special kind of leftmost derivation. If we use random permitting context grammars for all processes, we can only model a VBC formation during which information is introduced and processed locally and successively rather than being spread over different VBC processes.

  • 21.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Freund, Rudolf
    Hirvensalo, Mika
    Otto, Friedrich
    Non-Classical Models of Automata and Applications VI Preface2016In: Fundamenta Informaticae, ISSN 0169-2968, E-ISSN 1875-8681, Vol. 148, no 3-4, p. I-IIArticle in journal (Other academic)
  • 22.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hellström, Thomas
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    On ambiguity in learning from demonstration2010In: Intelligent Autonomous Systems 11 (IAS-11) / [ed] H. Christensen, F. Groen, and E. Petriu, Amsterdam: IOS Press , 2010, p. 47-56Conference paper (Refereed)
    Abstract [en]

    An overlooked problem in Learning From Demonstration is the ambiguity that arises, for instance, when the robot is equipped with more sensors than necessary for a certain task. Simply trying to repeat all aspects of a demonstration is seldom what the human teacher wants, and without additional information, it is hard for the robot to know which features are relevant and which should be ignored. This means that a single demonstration maps to several different behaviours the teacher might have intended. This one-to-many (or many-to-many) mapping from a demonstration (or several demonstrations) into possible intended behaviours is the ambiguity that is the topic of this paper. Ambiguity is defined as the size of the current hypothesis space. We investigate the nature of the ambiguity for different kinds of hypothesis spaces and how it is reduced by a new concept learning algorithm.

  • 23.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hellström, Thomas
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Towards Proactive Robot Behavior Based on Incremental Language Analysis2014In: MMRWHRI '14 Proceedings of the 2014 Workshop on Multimodal, Multi-Party, Real-World Human-Robot Interaction / [ed] Mary Ellen Foster, Manuel Giuliani, Ronald P. A. Petrick, 2014, p. 21-22Conference paper (Refereed)
    Abstract [en]

    This paper describes ongoing and planned work on incremental language processing coupled to inference of expected robot actions. Utterances are processed word-by-word, simultaneously with inference of expected robot actions, thus enabling the robot to prepare and act proactively to human utterances. We believe that such a model results in more natural human-robot communication since proactive behavior is a feature of human-human communication.

  • 24.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hoeberechts, Maia
    Ocean Networks Canada and Department of Computer Science, University of Victoria, Victoria, Canada.
    On the Degree of Nondeterminism of Tree Adjoining Languages and Head Grammar Languages2017In: Descriptional Complexity of Formal Systems: 19th IFIP WG 1.02 International Conference, DCFS 2017, Milano, Italy, July 3-5, 2017, Proceedings / [ed] Giovanni Pighizzini, Cezar Câmpeanu, 2017, p. 65-76Conference paper (Refereed)
    Abstract [en]

    The degree of nondeterminism is a measure of syntactic complexity which was investigated for parallel and sequential rewriting systems. In this paper, we consider the degree of nondeterminsm for tree adjoining grammars and their languages and head grammars and their languages. We show that a degree of nondeterminism of 2 suffices for both formalisms in order to generate all languages in their respective language families. Furthermore, we show that deterministic tree adjoining grammars (those with degree of nondeterminism equal to 1), can generate non-context-free languages, in contrast to deterministic head grammars which can only generate languages containing a single word. 

  • 25.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Holzer, Markus
    Institut für Informatik, Universität Giessen.
    Kutrib, Martin
    Institut für Informatik, Universität Giessen.
    Malcher, Andreas
    Institut für Informatik, Universität Giessen.
    Input-Driven Stack Automata2012In: IFIP TCS: Theoretical Computer Science - 7th IFIP TC 1/WG 2.2 International Conference, TCS 2012, Amsterdam, 2012. Proceedings / [ed] Jos C. M. Baeten, Thomas Ball, and Frank S. de Boer, 2012, p. 28-42Conference paper (Refereed)
    Abstract [en]

    We introduce and investigate input-driven stack automata, which are a generalization of input-driven pushdown automata that recently became popular under the name visibly pushdown automata. Basically, the idea is that the input letters uniquely determine the operations on the pushdown store. This can nicely be generalized to stack automata by further types of input letters which are responsible for moving the stack pointer up or down. While visibly pushdown languages share many desirable properties with regular languages, input-driven stack automata languages do not necessarily so. We prove that deterministic and non- deterministic input-driven stack automata have different computational power, which shows in passing that one cannot construct a deterministic input-driven stack automaton from a nondeterministic one. We study the computational capacity of these devices. Moreover, it is shown that the membership problem for nondeterministic input-driven stack automata languages is NP-complete.

  • 26.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Department of Computing Science.
    Jevtic, Aleksandar
    Institut de Robotica i Informatica Industrial, Technical University of Catalonia, Spain.
    Hellström, Thomas
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    On Interaction Quality in Human-Robot Interaction2017In: Proceedings of the 9th International Conference on Agents and Artificial Intelligence / [ed] H. Jaap van den Herik, Ana Paula Rocha, Joaquim Filipe, Setúbal: SciTePress, 2017, Vol. 1, p. 182-189Conference paper (Refereed)
    Abstract [en]

    In many complex robotics systems, interaction takes place in all directions between human, robot, and environment. Performance of such a system depends on this interaction, and a proper evaluation of a system must build on a proper modeling of interaction, a relevant set of performance metrics, and a methodology to combine metrics into a single performance value. In this paper, existing models of human-robot interaction are adapted to fit complex scenarios with one or several humans and robots. The interaction and the evaluation process is formalized, and a general method to fuse performance values over time and for several performance metrics is presented. The resulting value, denoted interaction quality, adds a dimension to ordinary performance metrics by being explicit about the interplay between performance metrics, and thereby provides a formal framework to understand, model, and address complex aspects of evaluation of human-robot interaction. 

  • 27.
    Bensch, Suna
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Kutrib, Martin
    Institut fuer Informatik, Universität Giessen.
    Malcher, Andreas
    Institut fuer Informatik, Universität Giessen.
    Extended Uniformly Limited T0L Languages and Mild Context-Sensitivity2016In: Eight Workshop on Non-Classical Models of Automata and Applications (NCMA 2016): Short Papers / [ed] Henning Bordihn, Rudolf Freund, Benedek Nagy, and György Vaszil, Wien: Institut für Computersprachen , 2016, p. 35-46Conference paper (Refereed)
    Abstract [en]

    We study the fixed membership problem for k-uniformly-limited and propagating ET0L systems (kulEPT0L systems). To this end, the algorithm given in [7] is applied. It follows that kulEPT0L languages are parsable in polynomial time. Since kulEPT0L languages are semi-linear [1] and kulEPT0L systems generate certain non-context-free languages, which capture the non-context-free phenomena occurring in natural languages, this is the last building block to show that kulEPT0L languages, for k ≥ 2, belong to the family of mildly context-sensitive languages.

  • 28. Hellström, Thomas
    et al.
    Bensch, Suna
    Modeling Interaction for Understanding in HRI2018In: Proceedings of Explainable Robotic Systems Workshop at HRI 2018, Chicago, USA, March 2018, 2018, 2018Conference paper (Refereed)
    Abstract [en]

    As robots become more and more capable and autonomous, there is an increased need for humans to understand what the robots do and think. In this paper we investigate what such understanding means and includes, and how robots are and can be designed to support understanding. We present a model of interaction for understanding. The aim is to provide a uniform formal understanding of the large body of existing work, and also to support continued work in the area.

  • 29.
    Hellström, Thomas
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Understandable Robots: What, Why, and How2018In: Paladyn - Journal of Behavioral Robotics, ISSN 2080-9778, E-ISSN 2081-4836, Vol. 9, no 1, p. 110-123Article in journal (Refereed)
    Abstract [en]

    As robots become more and more capable and autonomous, there is an increasing need for humans to understand what the robots do and think. In this paper, we investigate what such understanding means and in- cludes, and how robots can be designed to support un- derstanding. After an in-depth survey of related earlier work, we discuss examples showing that understanding includes not only the intentions of the robot, but also de- sires, knowledge, beliefs, emotions, perceptions, capabil- ities, and limitations of the robot. The term understandingis formally defined, and the term communicative actions is defined to denote the various ways in which a robot may support a human’s understanding of the robot. A novel model of interaction for understanding is presented. The model describes how both human and robot may utilize a first or higher-order theory of mind to understand each other and perform communicative actions in order to sup- port the other’s understanding. It also describes simpler cases in which the robot performs static communicative actions in order to support the human’s understanding of the robot. In general, communicative actions performed by the robot aim at reducing the mismatch between the mind of the robot, and the robot’s inferred model of the human’s model of the mind of the robot. Based on the pro- posed model, a set of questions are formulated, to serve as support when developing and implementing the model in real interacting robots.

  • 30.
    Sutherland, Alexander
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hellström, Thomas
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Inferring Robot Actions from Verbal Commands Using Shallow Semantic Parsing2015In: ICAI 2015: Proceedings of the 2015 International Conference on Artificial Intelligence, 2015, p. 28-34Conference paper (Refereed)
  • 31.
    Tewari, Maitreyee
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Natural Language Communication with Social Robots for Assisted Living2018Conference paper (Refereed)
    Abstract [en]

    We explore a new dialogue modelling approach for assistive social robots that enables us to formalize flexible conversation flows between a robot and a human. We achieve this by introducing an expectation mechanism to handle, for example, topic change, clarification questions or misunderstandings during a dialogue. The model gave us insight into the dialogue structure and how it is shaped by several linguistic and pragmatic features. This is work in progress and in the future we will explore learning algorithms that mine the features, implement and validate the model with real conversations. 

  • 32.
    Woldemariam, Yonas Demeke
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Björklund, Henrik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Predicting User Competence from Linguistic Data2017In: Proceedings of the 14th International Conference on Natural Language Processing (ICON-2017) / [ed] Sivaji Bandyopadhyay, Jadavpur University , 2017, p. 476-484Conference paper (Refereed)
    Abstract [en]

    We investigate the problem of predicting the competence of users of the crowd-sourcing platform Zooniverse by analyzing their chat texts. Zooniverse is an online platform where objects of different types are displayed to volunteer users to classify. Our research focuses on the Zoonivers Galaxy Zoo project, where users classify the images of galaxies and discuss their classifications in text. We apply natural language processing methods to extract linguistic features including syntactic categories, bag-of-words, and punctuation marks. We trained three supervised machine-learning classifiers on the resulting dataset: k-nearest neighbors, decision trees (with gradient boosting) and naive Bayes. They are evaluated (regarding accuracy and F-measure) with two different but related domain datasets. The performance of the classifiers varies across the feature set configurations designed during the training phase. A challenging part of this research is to compute the competence of the users without ground truth data available. We implemented a tool that estimates the proficiency of users and annotates their text with computed competence. Our evaluation results show that the trained classifier models give results that are significantly better than chance and can be deployed for other crowd-sourcing projects as well. 

  • 33.
    Woldemariam, Yonas Demeke
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Björklund, Henrik
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Bensch, Suna
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Predicting User Competence from Linguistic Data2017In: Proceedings of the 14th International Conference on Natural Language Processing (ICON-2017), NLP Association of India , 2017, p. 476-484Conference paper (Refereed)
    Abstract [en]

    We investigate the problem of predicting the competence of users of the crowdsourcing platform Zooniverse by analyzing their chat texts. Zooniverse is an online platform where objects of different types are displayed to volunteer users to classify. Our research focuses on the Zoonivers Galaxy Zoo project, where users classify the images of galaxies and discuss their classifications in text. We apply natural language processing methods to extract linguistic features including syntactic categories, bag-of-words, and punctuation marks. We trained three supervised machine-learning classifiers on the resulting dataset: k-nearest neighbors, decision trees (with gradient boosting) and naive Bayes. They are evaluated (regarding accuracy and F-measure) with two different but related domain datasets. The performance of the classifiers varies across the feature set configurations designed during the training phase. A challenging part of this research is to compute the competence of the users without ground truth data available. We implemented a tool that estimates the proficiency of users and annotates their text with computed competence. Our evaluation results show that the trained classifier models give results that are significantly better than chance and can be deployed for other crowd-sourcing projects as well.

1 - 33 of 33
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