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Found 16 papers, 3 papers with code
Mapping the Mind-Brain Duality to a Digital-Analog Perceptual Duality
We review existing data showing that cascades of neural circuits can convert between analog and digital signals, thereby linking physical and mental processes.
Towards Information Theory-Based Discovery of Equivariances
The presence of symmetries imposes a stringent set of constraints on a system.
Intrinsic Motivation in Dynamical Control Systems
Biological systems often choose actions without an explicit reward signal, a phenomenon known as intrinsic motivation.
Skilled motor control implies a low entropy of states but a high entropy of actions
The mastery of skills such as playing tennis or balancing an inverted pendulum implies a very accurate control of movements to achieve the task goals.
A space of goals: the cognitive geometry of informationally bounded agents
This induces a geometry that increasingly differs from the original geometry of the given world as information costs become increasingly important.
Causal blankets: Theory and algorithmic framework
We introduce a novel framework to identify perception-action loops (PALOs) directly from data based on the principles of computational mechanics.
AvE: Assistance via Empowerment
One difficulty in using artificial agents for human-assistive applications lies in the challenge of accurately assisting with a person's goal(s).
Human Perception of Intrinsically Motivated Autonomy in Human-Robot Interaction
A challenge in using robots in human-inhabited environments is to design behavior that is engaging, yet robust to the perturbations induced by human interaction.
Measuring Time with Minimal Clocks
Clock cascades show a "condensation effect" and the composite clock shows various regimes of markedly different dynamics.
Bold Hearts Team Description for RoboCup 2019 (Humanoid Kid Size League)
We participated in the RoboCup 2018 competition in Montreal with our newly developed BoldBot based on the Darwin-OP and mostly self-printed custom parts.
Expanding the Active Inference Landscape: More Intrinsic Motivations in the Perception-Action Loop
Research on intrinsic motivations may profit from an additional way to implement intrinsically motivated agents that also share the biological plausibility of active inference.
Action and perception for spatiotemporal patterns
This is a contribution to the formalization of the concept of agents in multivariate Markov chains.
Towards information based spatiotemporal patterns as a foundation for agent representation in dynamical systems
We present some arguments why existing methods for representing agents fall short in applications crucial to artificial life.
Changing the Environment Based on Empowerment as Intrinsic Motivation
In this paper we investigate how the information-theoretic measure of agent empowerment can provide a task-independent, intrinsic motivation to restructure the world.
Changing the Environment based on Intrinsic Motivation
One of the remarkable feats of intelligent life is that it restructures the world it lives in for its own benefit.
Empowerment -- an Introduction
This book chapter is an introduction to and an overview of the information-theoretic, task independent utility function "Empowerment", which is defined as the channel capacity between an agent's actions and an agent's sensors.
