# Active inference and epistemic value

@article{Friston2015ActiveIA, title={Active inference and epistemic value}, author={Karl J. Friston and Francesco Rigoli and Dimitri Ognibene and Christoph D Mathys and Thomas H. B. FitzGerald and Giovanni Pezzulo}, journal={Cognitive Neuroscience}, year={2015}, volume={6}, pages={187 - 214} }

We offer a formal treatment of choice behavior based on the premise that agents minimize the expected free energy of future outcomes. Crucially, the negative free energy or quality of a policy can be decomposed into extrinsic and epistemic (or intrinsic) value. Minimizing expected free energy is therefore equivalent to maximizing extrinsic value or expected utility (defined in terms of prior preferences or goals), while maximizing information gain or intrinsic value (or reducing uncertainty…

## 459 Citations

Active inference, Bayesian optimal design, and expected utility

- Computer ScienceArXiv
- 2021

This chapter describes how active inference combines Bayesian decision theory and optimal Bayesian design principles under a single imperative to minimize expected free energy to enable the natural emergence of information-seeking behavior.

Evidence for surprise minimization over value maximization in choice behavior

- Economics, PsychologyScientific reports
- 2015

It is shown that human decision-making is better explained by surprise minimization compared to utility maximization, and a limitation of purely economic motivations in explaining choice behavior is highlighted and the importance of belief-based motivations is emphasized.

Demystifying active inference

- Computer ScienceArXiv
- 2019

This review disambiguates properties of active inference, by providing a condensed overview of the theory underpinning active inference and noting that this formalism can be applied in other engineering applications; e.g., robotic arm movement, playing Atari games, etc., if appropriate underlying probability distributions can be formulated.

Active Inference and Epistemic Value in Graphical Models

- Computer ScienceFrontiers in Robotics and AI
- 2022

It is concluded that CBFE optimization by message passing suggests a general mechanism for epistemic-aware AIF in free-form generative models, similar to how an EFE agent incurs expected reward in significantly more environmental scenarios.

Prior Preference Learning from Experts: Designing a Reward with Active Inference

- Computer ScienceNeurocomputing
- 2022

Understanding the origin of information-seeking exploration in probabilistic objectives for control

- Computer ScienceArXiv
- 2021

This paper proposes a dichotomy in the objective functions underlying adaptive behaviour between evidence objectives, which correspond to well-known reward or utility maximizing objectives and their novel divergence objectives which instead seek to minimize the divergence between the agent's expected and desired distribution over futures and which give rise to information-seeking exploration.

Computational mechanisms of curiosity and goal-directed exploration

- PsychologybioRxiv
- 2018

This work illustrates the emergence of different types of information-gain, termed active inference and active learning, and shows how these forms of exploration induce distinct patterns of ‘Bayes-optimal’ behaviour.

Whence the Expected Free Energy?

- PhilosophyNeural Computation
- 2021

This letter investigates the origins of the EFE in detail and presents a functional that is argued is the natural extension of the VFE but actively discourages exploratory behavior, thus demonstrating that exploration does not directly follow from free energy minimization into the future.

Generalised free energy and active inference: can the future cause the past?

- Economics
- 2018

This work compares two free energy functionals for active inference under Markov decision processes and shows that policies are inferred or selected that realise prior preferences by minimising the free energy of future expectations.

Introducing a Bayesian model of selective attention based on active inference

- PsychologyScientific Reports
- 2019

A formal model of selective attention based on active inference and contextual epistemic foraging is introduced, which shows that the atypical exploratory behaviours in conditions such as autism and anxiety may be due to a failure to appropriately modulate sensory precision in a context-specific way.

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