Sophisticated Affective Inference: Simulating Anticipatory Affective Dynamics of Imagining Future Events
2020
In this paper, we combine sophisticated and deep-parametric active inference to create an agent whose affective states change as a consequence of its Bayesian beliefs about how possible future outcomes will affect future beliefs. To achieve this, we augment Markov Decision Processes with a Bayes-adaptive deep-temporal tree search that is guided by a free energy functional which recursively scores counterfactual futures. Our model reproduces the common phenomenon of rumination over a situation until unlikely, yet aversive and arousing situations emerge in one’s imagination. As a proof of concept, we show how certain hyperparameters give rise to neurocognitive dynamics that characterise imagination-induced anxiety.
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