Evidential Network with Conditional Belief Functions for an Adaptive Training in Informed Virtual Environment

1. Amokrane, K., Lourdeaux, D., Burkhardt, J.M.: HERA: Learner Tracking in a Virtual Environment. International Journal of Virtual Reality 7(3), 23–30 (2008)

   Google Scholar 

2. Ben Yaghlane, B., Mellouli, K.: Inference in directed evidential networks based on the transferable belief model. International Journal of Approximate Reasoning 48(2), 399–418 (2008)

   Article  MathSciNet  MATH  Google Scholar 

3. Buche, C., Bossard, C., Querrec, R., Chevaillier, P.: PEGASE: A Generic and Adaptable Intelligent System for Virtual Reality Learning Environments. International Journal of Virtual Reality 9(2), 73–85 (2010)

   Google Scholar 

4. Flipo, A.: TRUST: the Truck Simulator for Training. In: Driving Simulation Conference, Paris, France, 208–220 (2000)

   Google Scholar 

5. Mercier, D., Quost, B., Denoeux, T.: Refined modeling of sensor reliability in the belief function framework using contextual discounting. Information Fusion 9(2), 246–258 (2008)

   Article  Google Scholar 

6. Mufti-Alchawafa, D.: Modélisation et représentation de la connaissance pour la conception d’un systéme décisionnel dans un environnement informatique d’apprentissage en chirurgie. PhD thesis, Université Joseph Fourier - Grenoble I (2008)

   Google Scholar 

7. Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Francisco (1988)

   Google Scholar 

8. Ramasso, E., Rombaut, M., Pellerin, D.: Modéle des Croyances Transférables: Représentation des connaissances, Fusion d’informations, Décision. Technical report (2007)

   Google Scholar 

9. Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press (1976)

   Google Scholar 

10. Shenoy, P.P.: Using Dempster-Shafer’s belief-function theory in expert systems. In: Advances in the Dempster-Shafer theory of evidence, pp. 395–414. John Wiley & Sons (1994)

    Google Scholar 

11. Smets, P.: Belief functions: The disjunctive rule of combination and the generalized Bayesian theorem. International Journal of Approximate Reasoning 9(1), 1–35 (1993)

    Article  MathSciNet  MATH  Google Scholar 

12. Smets, P., Kennes, R.: The transferable belief model. Artificial Intelligence 66(2) (1994)

    Google Scholar 

13. Smets, P.: Decision making in the TBM: the necessity of the pignistic transformation. International Journal of Approximate Reasoning 38(2), 133–147 (2005)

    Article  MathSciNet  MATH  Google Scholar 

14. Smets, P.: Analyzing the combination of conflicting belief functions. Information Fusion 8(4), 387–412 (2007)

    Article  MathSciNet  Google Scholar 

15. Xu, H., Smets, P.: Evidential Reasoning with Conditional Belief Functions. In: Uncertainty in Artificial Intelligence, San Francisco, CA, pp. 598–605 (1994)

    Google Scholar 

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