ArticleFrontiers in neurorobotics2012
What is value-accumulated reward or evidence?
Article in Frontiers in neurorobotics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
18 citing papers in PubMed.
- Resolving uncertainty on the fly: modeling adaptive driving behavior as active inference.Frontiers in neurorobotics · 2024Article
- Interoception as modeling, allostasis as control.Biological psychology · 2022Article
- Embodied skillful performance: where the action is.Synthese · 2021Article
- Active inference on discrete state-spaces: A synthesis.Journal of mathematical psychology · 2020Review
- Learning action-oriented models through active inference.PLoS computational biology · 2020Article
- Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain.Frontiers in artificial intelligence · 2020Article
- Variational Free Energy and Economics Optimizing With Biases and Bounded Rationality.Frontiers in psychology · 2020Article
- Generalised free energy and active inference.Biological cybernetics · 2019Article
- The hierarchically mechanistic mind: an evolutionary systems theory of the human brain, cognition, and behavior.Cognitive, affective & behavioral neuroscience · 2019Review
- Caching mechanisms for habit formation in Active Inference.Neurocomputing · 2019Article
- Normativity of Predictions: A New Research Perspective.Frontiers in psychology · 2019Article
- Regimes of Expectations: An Active Inference Model of Social Conformity and Human Decision Making.Frontiers in psychology · 2019Article
- Deep temporal models and active inference.Neuroscience and biobehavioral reviews · 2018Article
- Affective-associative two-process theory: a neurocomputational account of partial reinforcement extinction effects.Biological cybernetics · 2017Article
- Deep temporal models and active inference.Neuroscience and biobehavioral reviews · 2017Review
- Active inference and learning.Neuroscience and biobehavioral reviews · 2016Review
- Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression.Frontiers in human neuroscience · 2016Article
- Value and reward based learning in neurorobots.Frontiers in neurorobotics · 2013Article
Corrections and comments
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3 authors.
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Abstract
Why are you reading this abstract? In some sense, your answer will cast the exercise as valuable-but what is value? In what follows, we suggest that value is evidence or, more exactly, log Bayesian evidence. This implies that a sufficient explanation for valuable behavior is the accumulation of evidence for internal models of our world. This contrasts with normative models of optimal control and reinforcement learning, which assume the existence of a value function that explains behavior, where (somewhat tautologically) behavior maximizes value. In this paper, we consider an alternative formulation-active inference-that replaces policies in normative models with prior beliefs about the (future) states agents should occupy. This enables optimal behavior to be cast purely in terms of inference: where agents sample their sensorium to maximize the evidence for their generative model of hidden states in the world, and minimize their uncertainty about those states. Crucially, this formulation resolves the tautology inherent in normative models and allows one to consider how prior beliefs are themselves optimized in a hierarchical setting. We illustrate these points by showing that any optimal policy can be specified with prior beliefs in the context of Bayesian inference. We then show how these prior beliefs are themselves prescribed by an imperative to minimize uncertainty. This formulation explains the saccadic eye movements required to read this text and defines the value of the visual sensations you are soliciting.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.