Skip to main content

A Spatio-Temporal Model Towards Ad-Hoc Collaborative Decision-Making

  • Chapter
  • First Online:

Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC,volume 0))

Abstract

For an autonomous agent, performing a task in a spatio-temporal environment often requires interaction with other agents. Such interaction can be initiated by ad-hoc collaborative planning and decision-making, which then leads to physical support on site. On-site collaboration is important for a variety of operations, such as search-and-rescue or pick-up-and-delivery. Tasks are performed through sequences of actions, and agents perceive possibilities for these actions in terms of affordances from the environment. Agent collaboration therefore requires the communication of affordances between agents with different capabilities. This paper introduces a spatio-temporal model for the decentralized decision-making of autonomous agents regarding on-site collaboration. Based on Janelle’s time-geographic perspective on communication modes, we demonstrate that different task situations lead to different spatiotemporal constraints on communication, involving both physical presence and telepresence. The application of such constraints leads to an optimized message distribution strategy and therefore efficient affordance communication with regard to maximizing support in performing a given task.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Sengupta, R. and R. Sieber, Geospatial Agents, Agents Everywhere ... Transactions in GIS, 2007. 11(4): p. 483-506.

    Article  Google Scholar 

  2. Russell, S. and P. Norvig, Artificial Intelligence: A Modern Approach. 2nd ed. Prentice Hall Series in Artificial Intelligence. 2003, London: Prentice Hall.

    Google Scholar 

  3. Wooldridge, M., Intelligent Agents, in Multiagent Systems - A Modern Approach to Distributed Artificial Intelligence, G. Weiss, Editor. 1999, MIT Press: Cambridge, MA. p. 27-77.

    Google Scholar 

  4. O'Sullivan, D., Geographical information science: agent-based models. Progress in Human Geography, 2008. 32(4): p. 541-550.

    Article  Google Scholar 

  5. Benenson, I. and P. Torrens, Geosimulation - Automata-based modeling of urban phenomena. 2004, Chichester, England: Wiley.

    Book  Google Scholar 

  6. Batty, M., J. Desyllas, and E. Duxbury, The discrete dynamics of small-scale spatial events: agent-based models of mobility in carnivals and street parades. International Journal of Geographic Information Science, 2003. 17(7): p. 673–97.

    Article  Google Scholar 

  7. Raubal, M., S. Winter, S. Teßmann, and C. Gaisbauer, Time geography for adhoc shared-ride trip planning in mobile geosensor networks. ISPRS Journal of Photogrammetry and Remote Sensing, 2007. 62(5): p. 366-381.

    Article  Google Scholar 

  8. Erol, K., J. Hendler, and D. Nau, Complexity results for HTN planning. Annals of Mathematics and Artificial Intelligence, 1996. 18(1): p. 69-93.

    Article  Google Scholar 

  9. Nittel, S., M. Duckham, and L. Kulik, Information dissemination in mobile adhoc geosensor networks, in Geographic Information Science - Third International Conference, GIScience 2004, M. Egenhofer, C. Freksa, and H. Miller, Editors. 2004, Springer: Berlin. p. 206-222.

    Google Scholar 

  10. Zhao, F. and L. Guibas, Wireless Sensor Networks. 2004, Amsterdam: Elsevier.

    Google Scholar 

  11. Sun, R., Prolegomena to Integrating Cognitive Modeling and Social Simulation, in Cognition and Multi-Agent Interaction, R. Sun, Editor. 2006, Cambridge University Press: New York, USA. p. 3-26.

    Google Scholar 

  12. Anderson, J., D. Bothell, M. Byrne, S. Douglass, C. Lebiere, and Y. Qin, An integrated theory of mind. Psychological Review, 2004. 111(4): p. 1036-1060.

    Article  Google Scholar 

  13. Newell, A., Unified Theories of Cognition. 1990, Cambridge, Massachusetts: Harvard University Press.

    Google Scholar 

  14. Sun, R., The CLARION Cognitive Architecture: Extending Cognitive Modeling to Social Simulation, in Cognition and Multi-Agent Interaction, R. Sun, Editor. 2006, Cambridge University Press: New York, USA. p. 79-99.

    Google Scholar 

  15. Schoder, D., K. Fischbach, and C. Schmitt, Core Concepts in Peer-to-Peer Networking, in Peer-to-Peer Computing: The Evolution of a Disruptive Technology, R. Subramanian and B. Goodman, Editors. 2005, Idea Group Inc.: Hershey, PA. p. 1-27.

    Google Scholar 

  16. Peng, J., M. Wu, X. Zhang, Y. Xie, F. Jiang, and Y. Liu, A Collaborative Multi-Agent Model with Knowledge-Based Communication for the RoboCupRescue Simulation. in International Symposium on Collaborative Technologies and Systems (CTS'06). 2006.

    Google Scholar 

  17. Luo, Y. and L. Bölöni. Children in the Forest: Towards a Canonical Problem of Spatio-Temporal Collaboration. in AAMAS'07, Int. Conference on Autonomous Agents and Multiagent Systems. 2007. Honolulu, Hawai'i, USA: IFAAMAS.

    Google Scholar 

  18. Broxvall, M., M. Gritti, A. Saffiotti, B.-S. Seo, and Y.-J. Cho, PEIS Ecology: Integrating Robots into Smart Environments. in IEEE International Conference on Robotics and Automation (ICRA). 2006. Orlando, Florida.

    Google Scholar 

  19. Winter, S. and S. Nittel, Ad-hoc shared-ride trip planning by mobile geosensor networks. International Journal of Geographical Information Science, 2006. 20(8): p. 899-916.

    Article  Google Scholar 

  20. Raubal, M., S. Winter, and C. Dorr, Decentralized Time Geography for Ad-Hoc Collaborative Planning, in Spatial Information Theory - 9th International Conference, COSIT 2009, Aber Wrac’h, France, September 2009, K. Stewart Hornsby, et al., Editors. 2009, Springer: Berlin. p. 436-452.

    Google Scholar 

  21. Gibson, J., The Ecological Approach to Visual Perception. 1979, Boston: Houghton Mifflin Company.

    Google Scholar 

  22. Norman, D., The Design of Everyday Things. 1988, New York: Doubleday.

    Google Scholar 

  23. Raubal, M., Ontology and epistemology for agent-based wayfinding simulation. International Journal of Geographical Information Science, 2001. 15(7): p. 653-665.

    Article  Google Scholar 

  24. Raubal, M. and R. Moratz, A functional model for affordance-based agents, in Towards Affordance-Based Robot Control - International Seminar, Dagstuhl Castle, Germany, June 5-9, 2006. Revised Papers E. Rome, J. Hertzberg, and G. Dorffner, Editors. 2008, Springer: Berlin. p. 91-105.

    Google Scholar 

  25. Stoffregen, T., Affordances and events. Ecological Psychology, 2000. 12: p. 1-28.

    Article  Google Scholar 

  26. Janowicz, K. and M. Raubal, Affordance-Based Similarity Measurement for Entity Types, in Spatial Information Theory - 8th International Conference, COSIT 2007, Melbourne, Australia, September 2007, S. Winter, et al., Editors. 2007, Springer: Berlin. p. 133-151.

    Google Scholar 

  27. Barsalou, L., Ad hoc categories. Memory & Cognition, 1983. 11: p. 211-227.

    Google Scholar 

  28. Hägerstrand, T., What about people in regional science? Papers of the Regional Science Association, 1970. 24: p. 7-21.

    Google Scholar 

  29. Ren, F. and M.-P. Kwan, Geovisualization of Human Hybrid Activity-Travel Patterns. Transactions in GIS, 2007. 11(5): p. 721-744.

    Article  Google Scholar 

  30. Raubal, M., H. Miller, and S. Bridwell, User-Centred Time Geography For Location-Based Services. Geografiska Annaler B, 2004. 86(4): p. 245-265.

    Article  Google Scholar 

  31. Miller, H., What about people in geographic information science?, in Re-Presenting Geographical Information Systems, P. Fisher and D. Unwin, Editors. 2005, John Wiley. p. 215-242.

    Google Scholar 

  32. Janelle, D., Impact of Information Technologies, in The Geography of Urban Transportation, S. Hanson and G. Giuliano, Editors. 2004, Guilford Press: New York. p. 86-112.

    Google Scholar 

  33. Dijkstra, E.W., A note on two problems in connection with graphs. Numerische Mathematik, 1959. 1(1): p. 269-271.

    Article  Google Scholar 

Download references

Acknowledgments

The comments from four anonymous reviewers provided useful suggestions to improve the content and clarity of the paper. Dr. Winter acknowledges support from the Australian Research Council, DP0878119.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Martin Raubal .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Raubal, M., Winter, S. (2010). A Spatio-Temporal Model Towards Ad-Hoc Collaborative Decision-Making. In: Painho, M., Santos, M., Pundt, H. (eds) Geospatial Thinking. Lecture Notes in Geoinformation and Cartography, vol 0. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12326-9_15

Download citation

Publish with us

Policies and ethics