By dynamic planning, we refer to the ability of the human brain to infer and impose motor
trajectories related to cognitive decisions. A recent paradigm, active inference, brings …

Scholars argue that artificial intelligence (AI) can generate genuine novelty and new
knowledge and, in turn, that AI and computational models of cognition will replace human …

Artificial intelligence (AI) now matches or outperforms human intelligence in an astonishing
array of games, tests, and cognitive tasks that involve high-level reasoning and thinking …

Active inference helps us simulate adaptive behavior and decision-making in biological and
artificial agents. Building on our previous work exploring the relationship between active …

We introduce a new software package for the Julia programming language, the library
ActiveInference. jl. To make active inference agents with Partially Observable Markov …

Abstract Concept normativity is a prominent subject of inquiry in the philosophical literature
on the nature of concepts. Concepts are said to be normative, in that the use of concepts to …

Inspired by animal navigation strategies, we introduce a novel computational model to
navigate and map a space rooted in biologically inspired principles. Animals exhibit …

We propose a novel framework for modelling strategic interactions between boundedly-
rational agents in complex, partially observable environments. Our approach introduces …

" Intrinsic motivation" refers to the capacity for intelligent systems to be motivated
endogenously, ie by features of agential architecture itself rather than by learned …

This thesis is based on the Active Inference Framework (AIF), a theoretical model of
information processing that views agents as inference machines. While a vast amount of …