Artificial Intelligence Review

, Volume 42, Issue 4, pp 945–964 | Cite as

A systematic literature review of the Teleo-Reactive paradigm

  • Jose Luis Morales
  • Pedro Sánchez
  • Diego Alonso


The Teleo-Reactive approach designed by N. J. Nilsson offers a high-level programming model for the development of reactive systems such as robotic vehicles. Teleo-Reactive programs are written in a way that allows engineers to define behaviour taking account of goals and changes in the state of the environment. Since Nilsson’s original definition, published in 1994, various researchers have used the Teleo-Reactive paradigm, either applied to a particular domain or extended by adding more capabilities to the original definition. This article provides a systematic literature review of 53 previous Teleo-Reactive-based studies in journals, conference proceedings and the like. The aim of this paper is to identify, appraise, select and synthesize all this high-quality research evidence relating to the use of the Teleo-Reactive paradigm. The literature has been systematically reviewed to offer an overview of the present state of this field of study and identify the principal results that have been obtained thanks to the Teleo-Reactive approach. Finally, this article details the challenges and difficulties that have to be overcome to ensure further advances in the use of this technique.


Teleo-Reactive formalism Reactive systems Systematic review 


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  1. Ali K, Leung K, Konik T, Choi D, Shapiro D (2009) Knowledge-directed theory revision. In: Proceedings of ILP-09Google Scholar
  2. Benson S, Nilsson NJ (1995) Reacting, planning, and learning in an autonomous agent. In: Furukawa K, Michie D, Muggleton S (eds) Machine intelligence, vol 14. The Claredon Press, OxfordGoogle Scholar
  3. Brereton P, Kitchenham BA, Budgen D, Turner M, Khalil M (2007) Lessons from applying the systematic literature review process within the software engineering domain. J Syst Softw 80: 571–583CrossRefGoogle Scholar
  4. Broda K (2000) Constructing Teleo-Reactive robot programs. In: Proceedings of ECAI-00Google Scholar
  5. Broda K, Hogger CH (2004a) Designing and simulating individual Teleo-Reactive agents. In: Proceedings of KI-04Google Scholar
  6. Broda K, Hogger CH (2004b) Policies for cloned teleo-reactive robots. In: Proceedings of MATES-04Google Scholar
  7. Broda K, Hogger CH (2005a) Determining and verifying good policies for cloned Teleo-Reactive agents. Int J Comput Syst Sci Eng 20: 249–258Google Scholar
  8. Broda K, Hogger CH (2005b) Abstract policy evaluation for reactive agents. In: Proceedings of SARA-05Google Scholar
  9. Broda K, Hogger CJ (2010) Designing effective policies for minimal agents. Comput J 53: 1184–1209CrossRefGoogle Scholar
  10. Broda K, Clark K, Miller, R, Russo A (2009) SAGE: a logical agent-based environment monitoring and control system. In: Proceedings of AmI-09Google Scholar
  11. Choi D, Langley P (2005) Learning teleoreactive logic programs from problem solving. In: Proceedings of ILP-05Google Scholar
  12. Coffey S, Clark K (2006) A hybrid, Teleo-Reactive architecture for robot control. In: Proceedings of MARS-06Google Scholar
  13. De Paola A, Fiduccia S, Gatani L, Pizzitola A, Storniolo P (2004) Introducing automated reasoning in network management. In: Proceedings of ICAISC-04Google Scholar
  14. Di Fatta G, Gaglio S, Presti G, Re G, Selvaggio I (2003) Distributed intelligent management of active networks. In: Proceedings of AI*AI-03Google Scholar
  15. Dongol B, Hayes IJ, Robinson PJ (2010) Reasoning about real-time Teleo-Reactive programs. Technical Report SSE-2010-01, Division of Systems and Software Engineering Research, The University of QueenslandGoogle Scholar
  16. Gamble C, Riddle S (2011) Dependability explicit metadata: extended report on properties, policies and exemplary application to case studies. Technical Report CS-TR-1248, The Newcastle UniversityGoogle Scholar
  17. Gordon E, Logan B (2003) A goal processing architecture for game agents. In: Proceedings of AAMAS-03Google Scholar
  18. Gubisch G, Steinbauer G, Weiglhofer M, Wotawa F (2008) A Teleo-Reactive architecture for fast, reactive and robust control of mobile robots. In: Proceedings of IEA/AIE-08Google Scholar
  19. Hawthorne J, Anthony R (2009) Using a Teleo-Reactive programming style to develop self-healing application. In: Proceedings of ICST-09Google Scholar
  20. Hawthorne J, Anthony R (2010) A methodology for the use of the Teleo-Reactive programming technique in autonomic computing. In: Proceedings of SND/ACIS-10Google Scholar
  21. Hawthorne J, Anthony R, Petridis M (2011) Improving the development process for Teleo-Reactive programming through advanced composition. In: Proceedings of ICAS-11Google Scholar
  22. Hayes IJ (2008) Towards reasoning about Teleo-Reactive programs for robust real-time systems. In: Proceedings on SERENE08Google Scholar
  23. Katz EP (1997) Extending the Teleo-Reactive paradigm for robotic agent task control using Zadehan (Fuzzy) logic. In: Proceedings of CIRA-97Google Scholar
  24. Katz EP (1998) A simplifying diagrammatic representation of crisp and fuzzy Teleo-Reactive semantic circuitry for application in robotic agent task control. In: Proceedings of the SMC-98Google Scholar
  25. Kitchenham BA (2004) Procedures for undertaking systematic reviews. Joint Technical Report TR/SE-0401, Computer Science Department, Keele University and National ICT Australia LtdGoogle Scholar
  26. Kochenderfer M (2002) Evolving Teleo-Reactive programs for block stacking using indexicals through genetic programming. Book chapter: genetic algorithms and genetic programming at Stanford BookstoreGoogle Scholar
  27. Kochenderfer M (2003) Evolving hierarchical and recursive teleo-reactive programs through genetic programming. In: Proceedings of EuroGP-03Google Scholar
  28. Könik T, Negin N, Ugur K (2009) Inductive generalization of analytically learned goal hierarchies. In: Proceedings of ILP-09Google Scholar
  29. Kowalski R, Sadri F (2011) Teleo-Reactive abductive logic programs. Technical Report. The Imperial College LondonGoogle Scholar
  30. Lamsweerde A (2009) Requirements engineering: from goals to UML models to software specifications. Wiley, EnglandGoogle Scholar
  31. Langley P, Choi D (2006) Learning recursive control programs from problem solving. J Mach Learn Res 7: 493–518zbMATHMathSciNetGoogle Scholar
  32. Lee J, Durfee EH (1994) Structured circuit semantics for reactive plan execution systems. In: Proceedings of AAAI-94, 1232-1237Google Scholar
  33. Li N, Choi D, Langley P (2007) Adding goal priorities to Teleoreactive logic programs. In: Proceedings of the international symposium on skill scienceGoogle Scholar
  34. Marinovic S, Twidle K, Dulay N (2010a) Teleo-Reactive workflows for pervasive healthcare. In: Proceedings of PerCom-10Google Scholar
  35. Marinovic S, Twidle K, Dulay N, Sloman M (2010b) Teleo-Reactive policies for managing human-centric pervasive services. In: Proceedings of CNSM-10Google Scholar
  36. McGann C, Py F, Rajan K, Thomas H, Henthorn R, McEwen R (2007) T-REX: a model-based architecture for AUV control. In: Proceedings of ICAPS-07Google Scholar
  37. McGann C, Py F, Rajan K, Thomas H, Henthorn R, McEwen R (2008) A deliberative architecture for AUV control. In: Proceedings of ICRA-08Google Scholar
  38. Mousavi SR, Broda K (2003) Simplification Of Teleo-Reactive sequences. Technical Report, Imperial College LondonGoogle Scholar
  39. Nilsson NJ (1992) Toward agent programs with circuit semantics. Tech. Report STAN-CS-92-1412, Dept- of Computer Science, Stanford UniversityGoogle Scholar
  40. Nilsson NJ (1994) Teleo-Reactive programs for agent control. J Artif Intell Res 1: 139–158Google Scholar
  41. Nilsson NJ (2000) Learning strategies for mid-level robot control: some preliminary considerations and experiments. Tech. Report, Stanford UniversityGoogle Scholar
  42. Nilsson NJ (2001) Teleo-Reactive programs and the triple-tower architecture. Electron Trans Artif Intell 5: 99–110Google Scholar
  43. Parmar A (2002) A logical measure of progress for planning. In: Proceedings of AAAI-02, 498-505Google Scholar
  44. Payne RJ (2008) RPL: a policy language For dynamic reconfiguration. In: Proceedings of SERENE-08Google Scholar
  45. Rajan K, Py F, McGann C (2010) Adaptive control of AUVs using onboard planning and execution. Sea Technology MagazineGoogle Scholar
  46. Russell SE, Carr D, Dragone M, O’Hare GM, Collier RW (2011) From bogtrotting to herding: a UCD perspective. Ann Math Artif Intell 61: 349–368CrossRefzbMATHGoogle Scholar
  47. Saigol Z, Py F, Rajan K, McGann C, Wyatt J, Dearden R (2010) Randomized testing for robotic plan execution for autonomous systems. In: Proceedings of IEEE/OES-10Google Scholar
  48. Salomaki B, Choi D, Nejati N, Langley P (2005) Learning Teleoreactive logic programs by observation. In: Proceedings of AAAI-05Google Scholar
  49. Sánchez P, Alonso D, Morales JM, Navarro PJ (2011) From Teleo-Reactive specifications to architectural components: a model-driven approach, Technical Report ref. DT-EXPLORE-05.rev0, Universidad Politécnica de CartagenaGoogle Scholar
  50. Selic B (2003) The pragmatics of model-driven development. IEEE Trans Softw Eng 20: 19–25CrossRefGoogle Scholar
  51. Soto F, Sánchez P, Mateo A, Alonso D, Navarro PJ (2011) An educational tool for implementing reactive systems following a goal-driven approach. Technical Report ref. DT-EXPLORE-06.rev0, Universidad Politécnica de CartagenaGoogle Scholar
  52. Srinivasan P (2002) Development of block-stacking Teleo-Reactive programs using genetic programming. Book chapter: genetic algorithms and genetic programming at Stanford BookstoreGoogle Scholar
  53. Szyperski C (2002) Component software: beyond object-oriented programming. Addison-Wesley, ReadingGoogle Scholar
  54. Twidle K, Marinovic S, Dulay N (2010) Teleo-Reactive policies in Ponder2. In: Proceedings of POLICY-10Google Scholar
  55. Vargas B (2008) Solving navigation tasks with learned Teleo-Reactive programs. In: Proceedings of IROS-08Google Scholar
  56. Vargas B (2009) Aprendizaje de Programas Teleo-Reactivos para Robótica Móvil. PhD Thesis, Instituto Nacional de Astrofísica, Óptica y ElectrónicaGoogle Scholar
  57. Vargas B, Morales EF (2009) Learning navigation Teleo-Reactive programs using behavioural cloning. In: Proceedings of ICM-09Google Scholar
  58. Weiglhofer M (2007) Extended Teleo-Reactive compiler. Online available at
  59. Zelek JS (1995) Teleo-Reactive autonomous mobile navigation. In: Proceedings of CCECE-95Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Jose Luis Morales
    • 1
  • Pedro Sánchez
    • 1
  • Diego Alonso
    • 1
  1. 1.DSIE Research Group, Universidad Politécnica de CartagenaCartagenaSpain

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