Daniel A. Braun

research

∙ 09/20/2023

Automatic Bat Call Classification using Transformer Networks

Automatically identifying bat species from their echolocation calls is a...

0 Frank Fundel, et al. ∙

research

∙ 11/14/2022

Hierarchically Structured Task-Agnostic Continual Learning

One notable weakness of current machine learning algorithms is the poor ...

0 Heinke Hihn, et al. ∙

research

∙ 06/29/2022

On the relation of order theory and computation in terms of denumerability

Computability on uncountable sets has no standard formalization, unlike ...

0 Pedro Hack, et al. ∙

research

∙ 06/28/2022

Computation as uncertainty reduction: a simplified order-theoretic framework

Although there is a somewhat standard formalization of computability on ...

0 Pedro Hack, et al. ∙

research

∙ 03/30/2022

On a geometrical notion of dimension for partially ordered sets

The well-known notion of dimension for partial orders by Dushnik and Mil...

0 Pedro Hack, et al. ∙

research

∙ 02/24/2022

Classification of preordered spaces in terms of monotones – Filling in the gaps

Following the recent introduction of new classes of monotones, like inje...

0 Pedro Hack, et al. ∙

research

∙ 10/25/2021

Mixture-of-Variational-Experts for Continual Learning

One significant shortcoming of machine learning is the poor ability of m...

0 Heinke Hihn, et al. ∙

research

∙ 07/30/2021

Representing Pareto optima in preordered spaces: from Shannon entropy to injective monotones

Shannon entropy is the most widely used measure of uncertainty. It is us...

0 Pedro Hack, et al. ∙

research

∙ 11/30/2020

Binary Classification: Counterbalancing Class Imbalance by Applying Regression Models in Combination with One-Sided Label Shifts

In many real-world pattern recognition scenarios, such as in medical app...

0 Peter Bellmann, et al. ∙

research

∙ 11/03/2020

Specialization in Hierarchical Learning Systems

Joining multiple decision-makers together is a powerful way to obtain mo...

0 Heinke Hihn, et al. ∙

research

∙ 04/24/2020

The Two Kinds of Free Energy and the Bayesian Revolution

The concept of free energy has its origins in 19th century thermodynamic...

0 Sebastian Gottwald, et al. ∙

research

∙ 10/31/2019

Hierarchical Expert Networks for Meta-Learning

The goal of meta-learning is to train a model on a variety of learning t...

0 Heinke Hihn, et al. ∙

research

∙ 07/26/2019

An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems

Information-theoretic bounded rationality describes utility-optimizing d...

0 Heinke Hihn, et al. ∙

research

∙ 04/08/2019

Bounded rational decision-making from elementary computations that reduce uncertainty

In its most basic form, decision-making can be viewed as a computational...

0 Sebastian Gottwald, et al. ∙

research

∙ 09/16/2018

Systems of bounded rational agents with information-theoretic constraints

Specialization and hierarchical organization are important features of e...

0 Sebastian Gottwald, et al. ∙

research

∙ 09/04/2018

Bounded Rational Decision-Making with Adaptive Neural Network Priors

Bounded rationality investigates utility-optimizing decision-makers with...

0 Heinke Hihn, et al. ∙

research

∙ 04/16/2018

An information-theoretic on-line update principle for perception-action coupling

Inspired by findings of sensorimotor coupling in humans and animals, the...

0 Zhen Peng, et al. ∙

research

∙ 04/07/2016

Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes

Information-theoretic principles for learning and acting have been propo...

0 Jordi Grau-Moya, et al. ∙

research

∙ 12/21/2015

Information-Theoretic Bounded Rationality

Bounded rationality, that is, decision-making and planning under resourc...

0 Pedro A. Ortega, et al. ∙

research

∙ 11/05/2015

Adaptive information-theoretic bounded rational decision-making with parametric priors

Deviations from rational decision-making due to limited computational re...

0 Jordi Grau-Moya, et al. ∙

research

∙ 12/24/2013

Bounded Rational Decision-Making in Changing Environments

A perfectly rational decision-maker chooses the best action with the hig...

0 Jordi Grau-Moya, et al. ∙

research

∙ 12/16/2013

Abstraction in decision-makers with limited information processing capabilities

A distinctive property of human and animal intelligence is the ability t...

0 Tim Genewein, et al. ∙

research

∙ 03/18/2013

Generalized Thompson Sampling for Sequential Decision-Making and Causal Inference

Recently, it has been shown how sampling actions from the predictive dis...

0 Pedro A. Ortega, et al. ∙

research

∙ 06/09/2012

A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function

We propose a novel Bayesian approach to solve stochastic optimization pr...

0 Pedro A. Ortega, et al. ∙

research

∙ 05/17/2012

Free Energy and the Generalized Optimality Equations for Sequential Decision Making

The free energy functional has recently been proposed as a variational p...

0 Pedro A. Ortega, et al. ∙

research

∙ 07/28/2011

Information, Utility & Bounded Rationality

Perfectly rational decision-makers maximize expected utility, but crucia...

0 Pedro A. Ortega, et al. ∙

research

∙ 02/16/2010

Convergence of Bayesian Control Rule

Recently, new approaches to adaptive control have sought to reformulate ...

0 Pedro A. Ortega, et al. ∙

research

∙ 02/07/2010

A Minimum Relative Entropy Controller for Undiscounted Markov Decision Processes

Adaptive control problems are notoriously difficult to solve even in the...

0 Pedro A. Ortega, et al. ∙

research

∙ 11/26/2009

A conversion between utility and information

Rewards typically express desirabilities or preferences over a set of al...

0 Pedro A. Ortega, et al. ∙

research

∙ 11/26/2009

A Bayesian Rule for Adaptive Control based on Causal Interventions

Explaining adaptive behavior is a central problem in artificial intellig...

0 Pedro A. Ortega, et al. ∙

Daniel A. Braun

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