Combining Planning and Action, Lessons from Robots and the Natural World

  • Jeremy BaxterEmail author
Part of the Cognitive Systems Monographs book series (COSMOS, volume 22)


Acting continuously and robustly in a complex environment is something that animals and people do every day but it is something that has proved to be very difficult to engineer into robotic systems. This paper looks at developments in architectures for combining planning and acting over the past 20 years and discusses the strengths and weaknesses of this approach for industrial applications. Several examples are given of ways in which theories from the natural world have influenced the development of robotic applications. In particular in line with the reason for this symposium the paper describes how the opinions of Aaron Sloman have influenced the author and his work. The paper discusses what steps still need to be made to realise systems capable of interacting reliably with the natural world and still carrying out useful tasks. These future steps also have the potential to expand our understanding of the mechanisms used by biological systems.


  1. Baxter J, Hepplewhite R (1999) Agents in tank battle simulations. Commun ACM 42:74–75CrossRefGoogle Scholar
  2. Baxter JW, Horn GS (2001) Executing group tasks despite losses and failures. In: Proceedings of the 10th conference on computer generated forces and behavioral, representation, pp 205–214Google Scholar
  3. Baxter JW, Horn GS, Leivers DP (2008) Fly-by-agent: controlling a pool of uavs via a multi-agent system. Know-Based Syst 21(3):232–237.
  4. Briel MVD, Sanchez R, Do MB, Kambhampati S (2004) Effective approaches for partial satisfaction (over-subscription) planning. AAAI Press, San Jose, pp 562–569Google Scholar
  5. Firby RJ (1989) Adaptive execution in complex dynamic worlds. Yale University (Tech. rep.)Google Scholar
  6. Gat E (2009) Non-linear sequencing. IEEE Aerosp Electron Syst Mag 24(3):41–46. doi: 10.1109/MAES.2009.4811088
  7. Georgeff MP, Ingrand FF (1989) Decision-making in an embedded reasoning system. In: Proceedings of the Eleventh international joint conference on artificial intelligence. Morgan Kaufmann, Detroit (Michigan), pp 972–978Google Scholar
  8. Landau YD (1979) Adaptive control: the model reference approach. Marcel Dekker Inc., New YorkzbMATHGoogle Scholar
  9. Lee J, Huber MJ, Durfee EH, Kenny PG (1994) Um-prs: an implementation of the procedural reasoning system for multirobot applications. In: Conference on intelligent robotics in field, factory, service, and space (CIRFFSS, pp 842–849Google Scholar
  10. Miller I, Campbell M, Huttenlocher D (2008) Team cornell’s skynet: Robust perception and planning in an urban environment. J Field Robot 25:493–527Google Scholar
  11. Musliner DJ, Durfee EH, Shin KG (1993) Circa: a cooperative intelligent real-time control architecture. IEEE Trans Syst Man Cybern 23:1561–1574CrossRefGoogle Scholar
  12. Pell B, Gat E, Keesing R, Muscettola N, Smith B (1997) Robust periodic planning and execution for autonomous spacecraft. In: Proceedings of IJCAI-97, IJCAI. Morgan Kaufman Publishers, pp 1234–1239Google Scholar
  13. Rao AS, Georgeff MP (1995) Bdi agents: from theory to practice. In: Proceedings of the first international conference on multi-agent systems (ICMAS-95), pp 312–319Google Scholar
  14. Real L (1990) Search theory and mate choice. i. models of single-sex discrimination. Am Nat 136:376404Google Scholar
  15. Russell SJ, Norvig P (2002) Artificial intelligence: a modern approach, 2nd edn. Prentice Hall, Englewood CliffsGoogle Scholar
  16. Wright IP, Sloman A, Beaudoin LP (1996) Towards a design-based analysis of emotional episodes. Philos Psychiatry Psychol 3(2):101–126CrossRefGoogle Scholar
  17. Yoon S, Fern R, Givan A (2007) Ff-replan: a baseline for probabilistic planning. In: Proceedings of the international conference on automated planning and scheduling, pp 352259Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Poynting InstituteUniversity of BirminghamBirminghamUK

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