Towards Tsallis Fully Probabilistic Design

Vyacheslav Kungurtsev; Giovanni Russo

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arXiv · 2602.23892

Towards Tsallis Fully Probabilistic Design

Vyacheslav Kungurtsev·Giovanni Russo

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Abstract

Fully Probabilistic design (FPD) is a powerful framework offering an elegant and unifying account of stochastic control, learning and decision-making. Here we introduce a generalized FPD framework, which we term as Tsallis FPD. Tsallis FPD uses Tsallis divergence in place of the Kullback-Leibler divergence that defines the standard FPD cost term. Tsallis divergence is a natural generalization of the KL divergence, rooted in non-extensive statistical mechanics and providing flexibility towards modeling stochastic processes with non-Gaussian tail behavior. After formulating Tsallis FPD, we present a double iteration scheme that performs a sequence of backwards inductions, rather than a single pass down the stages that constitutes the proven approach for classical FPD.

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BibTeX RIS

Vyacheslav Kungurtsev, Giovanni Russo. 2026-02-27. Towards Tsallis Fully Probabilistic Design. https://arxiv.org/abs/2602.23892

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