activity
20162025
most citedPyPhi: A toolbox for integrated information theory

128 citations · 326 across the 8 of their papers we have counts for

collaborators

9 papers

q-bio.NC2025

Intrinsic cause-effect power: the tradeoff between differentiation and specification

William G. P. Mayner, William Marshall, Giulio Tononi

Integrated information theory (IIT) starts from the existence of consciousness and characterizes its essential properties: every experience is intrinsic, specific, unitary, definit…

cs.AI2024★ 6 cited

Dissociating Artificial Intelligence from Artificial Consciousness

Graham Findlay, William Marshall, Larissa Albantakis +4

Developments in machine learning and computing power suggest that artificial general intelligence is within reach. This raises the question of artificial consciousness: if a comput…

q-bio.NC2022★ 15 cited

Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical terms

Larissa Albantakis, Leonardo Barbosa, Graham Findlay +13

This paper presents Integrated Information Theory (IIT) 4.0. IIT aims to account for the properties of experience in physical (operational) terms. It identifies the essential prope…

q-bio.NC2022★ 21 cited

System Integrated Information

William Marshall, Matteo Grasso, William GP Mayner +7

Integrated information theory (IIT) starts from consciousness itself and identifies a set of properties (axioms) that are true of every conceivable experience. The axioms are trans…

q-bio.NC2017★ 128 cited

PyPhi: A toolbox for integrated information theory

William G. P. Mayner, William Marshall, Larissa Albantakis +3

Integrated information theory provides a mathematical framework to fully characterize the cause-effect structure of a physical system. Here, we introduce PyPhi, a Python software p…

q-bio.QM2017★ 77 cited

How causal analysis can reveal autonomy in models of biological systems

William Marshall, Hyunju Kim, Sara I. Walker +2

Standard techniques for studying biological systems largely focus on their dynamical, or, more recently, their informational properties, usually taking either a reductionist or hol…

cs.AI2017

What caused what? A quantitative account of actual causation using dynamical causal networks

Larissa Albantakis, William Marshall, Erik Hoel +1

Actual causation is concerned with the question "what caused what?" Consider a transition between two states within a system of interacting elements, such as an artificial neural n…

q-bio.NC2016★ 78 cited

Black-boxing and cause-effect power

William Marshall, Larissa Albantakis, Giulio Tononi

Reductionism assumes that causation in the physical world occurs at the micro level, excluding the emergence of macro-level causation. We challenge this reductionist assumption by…

q-bio.NC2016★ 1 cited

Mysteries of Visual Experience

Jerome Feldman

Science is a crowning glory of the human spirit and its applications remain our best hope for social progress. But there are limitations to current science and perhaps to any scien…