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By Herrigel, Voloshynovskiy, Rytsar

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Nielsen increasing as the stability is higher. The reason is that, at relatively high stability, old observations become irrelevant to the current behaviour which determines the real predictive probability distribution. Hence, the estimation based on the whole history using HMM or Beta with decay 1 is worse than the estimation with the same parameters when the system is unstable, where both old and recent outcomes are relevant to the current behaviour. Observe also in the cases of high stability that HMM based estimation is better than Beta estimation for most values of decay.

Bm be two local interaction histories with respect to the same event structure ES. We write h ⊆ h if n ≤ m and for all i with 1 ≤ i ≤ n : ai ⊆ bi Definition 5 (Information continuity). A L(ES)-formula ϕ is called information-continuous if for any two local interaction histories h and h with h⊆h: KES,h |= ϕ → KES,h |= ϕ We can ensure the soundness of the calculation of the global trust state by keeping the fomula of every justification information-continuous. While this seems a severe restriction, we claim that in a lot of cases it is still favorable over the counting of outcomes of interactions.

Markov chains. Cambridge University Press, Cambridge (1997) 18. : A tutorial on hidden markov models and selected applications in speech recognition. Proceedings of the IEEE 77(2), 257–286 (1989) 19. : Towards a formal framework for computational trust. -P. ) FMCO 2006. LNCS, vol. 4709, pp. 175–184. Springer, Heidelberg (2007) 20. : Data Analysis: A Bayesian Tutorial (Oxford Science Publications). Oxford University Press, Oxford (1996) 21. : Travos: Trust and reputation in the context of inaccurate information sources.

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