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08/15/2023
Brain-Inspired Computational Intelligence via Predictive Coding
Artificial intelligence (AI) is rapidly becoming one of the key technolo...
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05/29/2023
Understanding Predictive Coding as an Adaptive Trust-Region Method
Predictive coding (PC) is a brain-inspired local learning algorithm that...
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04/07/2023
Attention: Marginal Probability is All You Need?
Attention mechanisms are a central property of cognitive systems allowin...
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02/16/2023
Pretraining Language Models with Human Preferences
Language models (LMs) are pretrained to imitate internet text, including...
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12/02/2022
Designing Ecosystems of Intelligence from First Principles
This white paper lays out a vision of research and development in the fi...
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08/15/2022
Preventing Deterioration of Classification Accuracy in Predictive Coding Networks
Predictive Coding Networks (PCNs) aim to learn a generative model of the...
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07/20/2022
Successor Representation Active Inference
Recent work has uncovered close links between between classical reinforc...
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05/23/2022
RL with KL penalties is better viewed as Bayesian inference
Reinforcement learning (RL) is frequently employed in fine-tuning large ...
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04/05/2022
Hybrid Predictive Coding: Inferring, Fast and Slow
Predictive coding is an influential model of cortical neural activity. I...
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12/03/2021
Active Inference in Robotics and Artificial Agents: Survey and Challenges
Active inference is a mathematical framework which originated in computa...
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09/02/2021
Habitual and Reflective Control in Hierarchical Predictive Coding
In cognitive science, behaviour is often separated into two types. Refle...
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08/30/2021
A Mathematical Walkthrough and Discussion of the Free Energy Principle
The Free-Energy-Principle (FEP) is an influential and controversial theo...
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07/27/2021
Predictive Coding: a Theoretical and Experimental Review
Predictive coding offers a potentially unifying account of cortical func...
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10/13/2020
Investigating the Scalability and Biological Plausibility of the Activation Relaxation Algorithm
The recently proposed Activation Relaxation (AR) algorithm provides a si...
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10/02/2020
Relaxing the Constraints on Predictive Coding Models
Predictive coding is an influential theory of cortical function which po...
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09/11/2020
Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain
The backpropagation of error algorithm (backprop) has been instrumental ...
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07/11/2020
Control as Hybrid Inference
The field of reinforcement learning can be split into model-based and mo...
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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...
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06/13/2020
Reinforcement Learning as Iterative and Amortised Inference
There are several ways to categorise reinforcement learning (RL) algorit...
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06/07/2020
Predictive Coding Approximates Backprop along Arbitrary Computation Graphs
Backpropagation of error (backprop) is a powerful algorithm for training...
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04/17/2020
Whence the Expected Free Energy?
The Expected Free Energy (EFE) is a central quantity in the theory of ac...
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02/28/2020
Reinforcement Learning through Active Inference
The central tenet of reinforcement learning (RL) is that agents seek to ...
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11/24/2019
Scaling active inference
In reinforcement learning (RL), agents often operate in partially observ...
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04/29/2019
Generative models as parsimonious descriptions of sensorimotor loops
The Bayesian brain hypothesis, predictive processing and variational fre...
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03/22/2019
Nonmodular architectures of cognitive systems based on active inference
In psychology and neuroscience it is common to describe cognitive system...
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03/13/2015
