
The Two Kinds of Free Energy and the Bayesian Revolution
The concept of free energy has its origins in 19th century thermodynamic...
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Hierarchical Expert Networks for MetaLearning
The goal of metalearning is to train a model on a variety of learning t...
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An Informationtheoretic Online Learning Principle for Specialization in Hierarchical DecisionMaking Systems
Informationtheoretic bounded rationality describes utilityoptimizing d...
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Bounded rational decisionmaking from elementary computations that reduce uncertainty
In its most basic form, decisionmaking can be viewed as a computational...
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Systems of bounded rational agents with informationtheoretic constraints
Specialization and hierarchical organization are important features of e...
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Bounded Rational DecisionMaking with Adaptive Neural Network Priors
Bounded rationality investigates utilityoptimizing decisionmakers with...
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An informationtheoretic online update principle for perceptionaction coupling
Inspired by findings of sensorimotor coupling in humans and animals, the...
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Planning with InformationProcessing Constraints and Model Uncertainty in Markov Decision Processes
Informationtheoretic principles for learning and acting have been propo...
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InformationTheoretic Bounded Rationality
Bounded rationality, that is, decisionmaking and planning under resourc...
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Adaptive informationtheoretic bounded rational decisionmaking with parametric priors
Deviations from rational decisionmaking due to limited computational re...
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Bounded Rational DecisionMaking in Changing Environments
A perfectly rational decisionmaker chooses the best action with the hig...
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Abstraction in decisionmakers with limited information processing capabilities
A distinctive property of human and animal intelligence is the ability t...
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Generalized Thompson Sampling for Sequential DecisionMaking and Causal Inference
Recently, it has been shown how sampling actions from the predictive dis...
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A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function
We propose a novel Bayesian approach to solve stochastic optimization pr...
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Free Energy and the Generalized Optimality Equations for Sequential Decision Making
The free energy functional has recently been proposed as a variational p...
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Information, Utility & Bounded Rationality
Perfectly rational decisionmakers maximize expected utility, but crucia...
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Convergence of Bayesian Control Rule
Recently, new approaches to adaptive control have sought to reformulate ...
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A Minimum Relative Entropy Controller for Undiscounted Markov Decision Processes
Adaptive control problems are notoriously difficult to solve even in the...
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A conversion between utility and information
Rewards typically express desirabilities or preferences over a set of al...
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A Bayesian Rule for Adaptive Control based on Causal Interventions
Explaining adaptive behavior is a central problem in artificial intellig...
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