A Companion Technology for Cognitive Technical Systems

  • Andreas Wendemuth
  • Susanne Biundo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7403)


The Transregional Collaborative Research Centre SFB/TRR 62 ”A Companion Technology for Cognitive Technical Systems”, funded by the German Research Foundation (DFG) at Ulm and Magdeburg sites, deals with the systematic and interdisciplinary study of cognitive abilities and their implementation in technical systems. The properties of multimodality, individuality, adaptability, availability, cooperativeness and trustworthiness are at the focus of the investigation. These characteristics show a new type of interactive device which is not only practical and efficient to operate, but as well agreeable, hence the term ”companion”. The realisation of such a technology is supported by technical advancement as well as by neurobiological findings. Companion technology has to consider the entire situation of the user, machine, environment and (if applicable) other people or third interacting parties, in current and historical states. This will reflect the mental state of the user, his embeddedness in the task, and how he is situated in the current process.


Ventral Tegmental Area Skin Conductance Level Multimodal Interaction Markov Logic Network Plan Repair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Picard, R.: Affective Computing. The MIT Press, Cambridge (2007) ISBN 0-262-16170-2Google Scholar
  2. 2.
    Cowie, R. (coordinator): EU-IST Network of Excellence HUMAINE (The Human Machine Interaction Network on Emotion) (2004-2007), emotion-research.net
  3. 3.
    Wilks, Y. (coordinator): EU-IST Integrated Project IST-34434 COMPANIONS (2006-2010), companions-project.org
  4. 4.
    Wendemuth, A., Braun, J., Michaelis, B., Ohl, F., Rösner, D., Scheich, H., Warnemünde, R.: Neurobiologically Inspired, Multimodal Intention Recognition for Technical Communication Systems (NIMITEK). In: André, E., Dybkjær, L., Minker, W., Neumann, H., Pieraccini, R., Weber, M. (eds.) PIT 2008. LNCS (LNAI), vol. 5078, pp. 141–144. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  5. 5.
    Ghallab, M., Nau, D., Traverso, P.: Automated Planning: Theory & Practice. Morgan Kaufmann Publishers Inc., San Francisco (2004) ISBN 1558608567 Google Scholar
  6. 6.
    Biundo, S., Bercher, P., Geier, T., Müller, F., Schattenberg, B.: Advanced user assistance based on AI planning. Cognitive Systems Research 12(3-4), 219–236 (2011)CrossRefGoogle Scholar
  7. 7.
    Penberthy, J., Weld, D.: UCPOP: A Sound, Complete, Partial Order Planner for ADL. In: Proceedings of the Third International Conference on Knowledge Representation and Reasoning, pp. 103–114 (1992)Google Scholar
  8. 8.
    Nau, D., Au, T., Ilghami, O., Kuter, U., Muñoz-Avila, H., Murdock, J., Wu, D., Yaman, F.: Applications of SHOP and SHOP2. IEEE Intelligent Systems (2004)Google Scholar
  9. 9.
    Biundo, S., Schattenberg, B.: From Abstract Crisis to Concrete Relief (A Preliminary Report on Combining State Abstraction and HTN Planning). In: Proceedings of the 6th European Conference on Planning (ECP 2001), pp. 157–168. Springer (2001)Google Scholar
  10. 10.
    Coles, A., Coles, A.: LPRPG-P: Relaxed Plan Heuristics for Planning with Preferences. In: Proceedings of the 21st International Conference on Automated Planning and Scheduling (ICAPS 2011), pp. 26–33 (2011)Google Scholar
  11. 11.
    Bercher, P., Biundo, S.: Hybrid Planning with Preferences Using a Heuristic for Partially Ordered Plans. In: 26th PuK Workshop ”Planen, Scheduling und Konfigurieren, Entwerfen”, PuK 2011 (2011)Google Scholar
  12. 12.
    Sanner, S., Kersting, K.: Symbolic dynamic programming for first-order POMDPs. In: Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2010), pp. 1140–1146 (2010)Google Scholar
  13. 13.
    Müller, F., Biundo, S.: HTN-Style Planning in Relational POMDPs Using First-Order FSCs. In: Bach, J., Edelkamp, S. (eds.) KI 2011. LNCS, vol. 7006, pp. 216–227. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  14. 14.
    Bidot, J., Schattenberg, B., Biundo, S.: Plan Repair in Hybrid Planning. In: Dengel, A.R., Berns, K., Breuel, T.M., Bomarius, F., Roth-Berghofer, T.R. (eds.) KI 2008. LNCS (LNAI), vol. 5243, pp. 169–176. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  15. 15.
    Ilango, A., Shumake, J., Wetzel, W., Scheich, H., Ohl, F.: Effects of ventral tegmental area stimulation on the acquisition and long-term retention of active avoidance learning. Behav. Brain Res. 225(2), 515–521 (2011)CrossRefGoogle Scholar
  16. 16.
    Schulz, A., Schattenberg, B., Woldeit, M., Brechmann, A., Biundo, S., Ohl, F.W.: Reinforcement learning and planning models for two-way-avoidance and reversal learning. In: Proc. Annual Meeting of the Society For Neuroscience, Washington, USA (2011)Google Scholar
  17. 17.
    Richardson, M., Domingos, P.: Markov logic networks. Machine Learning 62(1-2), 107–136 (2006)CrossRefGoogle Scholar
  18. 18.
    Geier, T., Biundo, S.: Approximate Online Inference for Dynamic Markov Logic Networks. In: Proceedings of the 23rd IEEE International Conference on Tools with Artificial Intelligence, pp. 764–768 (2011)Google Scholar
  19. 19.
    Glodek, M., Bigalke, L., Palm, G., Schwenker, F.: Recognizing Human Activities Using a Layered HMM Architecture. Machine Learning Reports 5, 38–41 (2011)Google Scholar
  20. 20.
    Miller, R.B.: Response time in man-computer conversational transactions. In: Proceedings AFIPS Spring Joint Computer Conference, Montvale, pp. 267–277 (1968)Google Scholar
  21. 21.
    Clark, H.H., Brenan, S.E.: Grounding in communication. In: Resnick, L.B., Levine, J.M., Behrend, S.D. (eds.) Perspectives on Socially Shared Cognition, 1st edn., pp. 127–149. Amer Psychological Assn., Washington (1991)CrossRefGoogle Scholar
  22. 22.
    Kohrs, C., Behne, N., Scheich, H., Brechmann, A.: Similiar fMRI activation by delayed and omitted visual feedback. In: Proceedings of the Annual Meeting of the Society For Neuroscience, Chicago, USA (2009)Google Scholar
  23. 23.
    Kohrs, C., Angenstein, N., Scheich, H., Brechmann, A.: The temporal contingency of feedback: effects on brain activity. In: Proceedings of the International Conference on Aging and Cognition, Dortmund, Germany (2010)Google Scholar
  24. 24.
    Oviatt, S.: Multimodal Interfaces. In: Sears, A., Jacko, J. (eds.) The Human-Computer Interaction Handbook, 2nd edn., pp. 413–432. CRC Press, Boca Raton (2008)Google Scholar
  25. 25.
    Gram, C., Cockton, G.: Design principles for interactive software. Chapman & Hall, Ltd., London (1997) ISBN 0-412-72470-7Google Scholar
  26. 26.
    Scherer, S., Schels, M., Palm, G.: How Low Level Observations Can Help to Reveal the User’s State in HCI. In: D’Mello, S., Graesser, A., Schuller, B., Martin, J.-C. (eds.) ACII 2011, Part II. LNCS, vol. 6975, pp. 81–90. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  27. 27.
    Walter, S., Scherer, S., Schels, M., Glodek, M., Hrabal, D., Schmidt, M., Böck, R., Limbrecht, K., Traue, H.C., Schwenker, F.: Multimodal Emotion Classification in Naturalistic User Behavior. In: Jacko, J.A. (ed.) HCII 2011, Part III. LNCS, vol. 6763, pp. 603–611. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  28. 28.
    Glodek, M., Scherer, S., Schwenker, F., Palm, G.: Conditioned Hidden Markov Model Fusion for Multimodal Classification. In: ISCA (publ.): Proceedings of Interspeech 2011, pp. 2269–2272 (2011)Google Scholar
  29. 29.
    Wolff, S., Kohrs, C., Scheich, H., Brechmann, A.: Temporal contingency and prosodic modulation of feedback in human-computer interaction: Effects on brain activation and performance in cognitive tasks. In: Heiss, H., Pepper, P., Schlingloff, H., Schneider, J.(eds.): Informatik 2011 - Informatik schafft Communities: 41. Jahrestagung der GI, 4.-7.10. LNI P-192. Springer, Berlin (2011)Google Scholar
  30. 30.
    Rösner, D., Friesen, R., Otto, M., Lange, J., Haase, M., Frommer, J.: Intentionality in Interacting with Companion Systems – An Empirical Approach. In: Jacko, J.A. (ed.) HCII 2011, Part III. LNCS, vol. 6763, pp. 593–602. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  31. 31.
    Tan, J., Walter, S., Scheck, A., Hrabal, D., Hoffmann, H., Kessler, H., Traue, H.: Repeatability of facial electromygraphy (EMG) activity over corrugator supercilii and zygomaticus major on differentiating various emotions. Journal of Ambient Intelligence and Humanized Computing (2011) onlineGoogle Scholar
  32. 32.
    Siegert, I., Böck, R., Philippou-Hübner, D., Vlasenko, B., Wendemuth, A.: Approriate emotional Labelling of non-acted speech using basic emotions, Geneva emotion wheel and self-assessment maninkins. In: Proceedings of the 2011 IEEE International Conference on Multimedia & Expo. (ICME 2011), Barcelona, Spain, July 11-15, pp. 1–6 (2011)Google Scholar
  33. 33.
    Scherer, S., Glodek, M., Schwenker, F., Campbell, N., Palm, G.: Spotting Laughter in naturalistic multiparty conversations: a comparison of automatic online and offline approaches using audiovisual data. To appear in ACM Transactions on Interactive Intelligent Systems: Special Issue on Affective Interaction in Natural Environments (2011)Google Scholar
  34. 34.
    Al-Hamadi, A., Rashid, O., Michaelis, B.: Posture Recognition using Combined Statistical an Geometrical Feature Vectors based on SVM. International Journal of Information and Mathematical Sciences 6, 7–14 (2010)Google Scholar
  35. 35.
    Rashid, O., Al-Hamadi, A., Michaelis, B.: Integration of Gesture and Posture Recognition Systems for Interpreting Dynamic Meanings using Particle Filter. In: International Conference on Soft Computing and Pattern Recognition, Paris, pp. 47–50 (2010)Google Scholar
  36. 36.
    Layher, G., Liebau, H., Niese, R., Al-Hamadi, A., Michaelis, B., Neumann, H.: Robust Stereoscopic Head Pose Estimation in Human-Computer Interaction and a Unified Evaluation Framework. In: Maino, G., Foresti, G.L. (eds.) ICIAP 2011, Part I. LNCS, vol. 6978, pp. 227–236. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  37. 37.
    Glodek, M., Tschechne, S., Layher, G., Schels, M., Brosch, T., Scherer, S., Kächele, M., Schmidt, M., Neumann, H., Palm, G., Schwenker, F.: Multiple Classifier Systems for the Classification of Audio-Visual Emotional States. In: D’Mello, S., Graesser, A., Schuller, B., Martin, J.-C. (eds.) ACII 2011, Part II. LNCS, vol. 6975, pp. 359–368. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  38. 38.
    Schuller, B., Valstar, M., Cowie, R., Pantic, M.: The First Audio/Visual Emotion Challenge and Workshop – An Introduction. In: D’Mello, S., Graesser, A., Schuller, B., Martin, J.-C. (eds.) ACII 2011, Part II. LNCS, vol. 6975, p. 322. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  39. 39.
    Reuter, S., Dietmayer, K.: Pedestrian Tracking Using Random Finite Sets. In: 14. International Conference on Information Fusion, Chicago, pp. 1–8 (2011) ISBN: 978-1-4577-0267-9Google Scholar
  40. 40.
    Layher, G., Tschechne, S., Scherer, S., Brosch, T., Curio, C., Neumann, H.: Social Signal Processing in Companion Systems - Challenges Ahead. In: Heiss, H., Pepper, P., Schlingloff, H., Schneider, J.(eds.): Informatik 2011 - Informatik schafft Communities: 41. Jahrestagung der GI, 4.-7.10. LNI P-192. Springer, Berlin (2011)Google Scholar
  41. 41.
    Goldkuhl, G., Lind, M.: A Multi-Grounded Design Research Process. In: Winter, R., Zhao, J.L., Aier, S. (eds.) DESRIST 2010. LNCS, vol. 6105, pp. 45–60. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  42. 42.
    van Hoof, J., Kort, H.S.M., Rutten, P., Duijnstee, M.: Ageing-in-place with the use of ambient intelligence technology: Perspectives of older users. International Journal of Medical Informatics 80(5), 310–331 (2011)CrossRefGoogle Scholar
  43. 43.
    Organization for Economic Cooperation and Development (OECD) (publ.): Long-Term Care for Older People: The OECD Health Project. OECD Publishing, Paris (2005) ISBN: 92-64-00848-9Google Scholar
  44. 44.
    Scherer, M.: Rehabilitation psychology. Corsini Encyclopedia of Psychology, pp. 1-3. Wiley Online Library (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Andreas Wendemuth
    • 1
  • Susanne Biundo
    • 2
  1. 1.Cognitive SystemsOtto-von-Guericke UniversityMagdeburgGermany
  2. 2.Institute for Artificial IntelligenceUniversity of UlmUlmGermany

Personalised recommendations