Alexander Tschantz | DeepAI

DeepAI AI Chat

Featured Co-authors

Jun Tani
31 publications
Beren Millidge
28 publications
Christopher L. Buckley
26 publications
Karl Friston
24 publications
Pablo Lanillos
23 publications
Toby St. Clere Smithe
11 publications
Karl J. Friston
9 publications
Brennan Klein
8 publications
Anil K. Seth
8 publications
Ajith Anil Meera
7 publications
Steven Swanson
7 publications

∙ 12/02/2022

Designing Ecosystems of Intelligence from First Principles

This white paper lays out a vision of research and development in the fi...

0 Karl J. Friston, et al. ∙

∙ 04/05/2022

Hybrid Predictive Coding: Inferring, Fast and Slow

Predictive coding is an influential model of cortical neural activity. I...

0 Alexander Tschantz, et al. ∙

∙ 01/11/2022

pymdp: A Python library for active inference in discrete state spaces

Active inference is an account of cognition and behavior in complex syst...

69 Conor Heins, et al. ∙

∙ 12/03/2021

Active Inference in Robotics and Artificial Agents: Survey and Challenges

Active inference is a mathematical framework which originated in computa...

19 Pablo Lanillos, et al. ∙

∙ 03/11/2021

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

The exploration-exploitation trade-off is central to the description of ...

0 Beren Millidge, et al. ∙

∙ 02/19/2021

Neural Kalman Filtering

The Kalman filter is a fundamental filtering algorithm that fuses noisy ...

0 Beren Millidge, et al. ∙

∙ 10/13/2020

Investigating the Scalability and Biological Plausibility of the Activation Relaxation Algorithm

The recently proposed Activation Relaxation (AR) algorithm provides a si...

0 Beren Millidge, et al. ∙

∙ 10/02/2020

Relaxing the Constraints on Predictive Coding Models

Predictive coding is an influential theory of cortical function which po...

0 Beren Millidge, et al. ∙

∙ 09/11/2020

Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain

The backpropagation of error algorithm (backprop) has been instrumental ...

15 Beren Millidge, et al. ∙

∙ 07/11/2020

Control as Hybrid Inference

The field of reinforcement learning can be split into model-based and mo...

1 Alexander Tschantz, et al. ∙

∙ 06/23/2020

On the Relationship Between Active Inference and Control as Inference

Active Inference (AIF) is an emerging framework in the brain sciences wh...

0 Beren Millidge, et al. ∙

∙ 06/13/2020

Reinforcement Learning as Iterative and Amortised Inference

There are several ways to categorise reinforcement learning (RL) algorit...

0 Beren Millidge, et al. ∙

∙ 06/07/2020

Predictive Coding Approximates Backprop along Arbitrary Computation Graphs

Backpropagation of error (backprop) is a powerful algorithm for training...

0 Beren Millidge, et al. ∙

∙ 04/17/2020

Whence the Expected Free Energy?

The Expected Free Energy (EFE) is a central quantity in the theory of ac...

0 Beren Millidge, et al. ∙

∙ 02/28/2020

Reinforcement Learning through Active Inference

The central tenet of reinforcement learning (RL) is that agents seek to ...

0 Alexander Tschantz, et al. ∙

∙ 11/24/2019

Scaling active inference

In reinforcement learning (RL), agents often operate in partially observ...

0 Alexander Tschantz, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world