On efficient computation in active inference
The paper addresses challenges in employing active inference for intelligent behavior due to high computational costs and target distribution specific…
Chats
Causal Inference via Predictive Coding
The paper presents a novel approach to causal inference using predictive coding, a method inspired by neuroscience. By modifying the inference process…
Inferring Hierarchical Structure in Multi-Room Maze Environments
The paper presents a hierarchical active inference model that enhances navigation and exploration in multi-room environments using cognitive maps. It …
Intra-Active Inference I: Fundamentals
This paper, the first in a series, explores the application of new materialism to the free energy principle (FEP). It highlights the interplay between…
Active Inference in Hebbian Learning Networks
This research explores active inference using brain-inspired Hebbian learning networks to control agents. It describes a dual-network system that lear…
Designing explainable artificial intelligence with active inference: A framework for transparent introspection and decision-making
The paper explores the development of explainable AI systems using active inference, emphasizing transparency in decision-making and introspection. It…
Realising Synthetic Active Inference Agents, Part II: Variational Message Updates
This paper continues the exploration of synthetic Active Inference (AIF) agents as detailed in Part I, focusing on variational message updates. It hig…
On Embedded Normativity-An Active Inference account of agency beyond flesh
The paper introduces "embedded normativity" within the Active Inference framework, proposing that social norms emerge through human interaction with t…
Fusing event-based camera and radar for SLAM using spiking neural networks with continual STDP learning
The study introduces a novel SLAM architecture combining event-based cameras and FMCW radar for drone navigation, utilizing bio-inspired Spiking Neura…
Computing with Categories in Machine Learning
The paper introduces DisCoPyro, a framework combining category theory with amortized variational inference for machine learning. It bridges the gap be…