If a cognitive architecture implements Bayesian probability theory to model beliefs, which outcome will occur if the architecture receives conflicting sensory data?

💡 Explanation

Bayesian probability theory dictates beliefs update by combining prior beliefs with new evidence. Because Bayes' theorem provides a mechanism for weighting new sensory inputs against existing priors, the belief state will be updated accordingly rather than remaining static or oscillating; therefore, beliefs update according to priors.

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