128 citations · 444 across the 16 of their papers we have counts for
17 papers
On the utility of toy models for theories of consciousness
Larissa Albantakis
Toy models are highly idealized and deliberately simplified models that retain only the essential features of a system in order to explore specific theoretical questions. Long used…
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…
Measuring the integrated information of a quantum mechanism
Larissa Albantakis, Robert Prentner, Ian Durham
Originally conceived as a theory of consciousness, integrated information theory (IIT) provides a theoretical framework intended to characterize the compositional causal informatio…
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…
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…
Only what exists can cause: An intrinsic powers view of free will
Giulio Tononi, Larissa Albantakis, Melanie Boly +3
This essay addresses the implications of integrated information theory (IIT) for free will. IIT is a theory of what consciousness is and of how its presence and quality can be acco…
What we are is more than what we do
Larissa Albantakis, Giulio Tononi
If we take the subjective character of consciousness seriously, consciousness becomes a matter of "being" rather than "doing". Because "doing" can be dissociated from "being", func…
A macro agent and its actions
Larissa Albantakis, Francesco Massari, Maggie Beheler-Amass +1
In science, macro level descriptions of the causal interactions within complex, dynamical systems are typically deemed convenient, but ultimately reducible to a complete causal acc…
When is an action caused from within? Quantifying the causal chain leading to actions in simulated agents
Bjørn Erik Juel, Renzo Comolatti, Giulio Tononi +1
An agent's actions can be influenced by external factors through the inputs it receives from the environment, as well as internal factors, such as memories or intrinsic preferences…
How swarm size during evolution impacts the behavior, generalizability, and brain complexity of animats performing a spatial navigation task
Dominik Fischer, Sanaz Mostaghim, Larissa Albantakis
While it is relatively easy to imitate and evolve natural swarm behavior in simulations, less is known about the social characteristics of simulated, evolved swarms, such as the op…
The Role of Conditional Independence in the Evolution of Intelligent Systems
Jory Schossau, Larissa Albantakis, Arend Hintze
Systems are typically made from simple components regardless of their complexity. While the function of each part is easily understood, higher order functions are emergent properti…
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…
Markov Brains: A Technical Introduction
Arend Hintze, Jeffrey A. Edlund, Randal S. Olson +9
Markov Brains are a class of evolvable artificial neural networks (ANN). They differ from conventional ANNs in many aspects, but the key difference is that instead of a layered arc…
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…
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…
A Tale of Two Animats: What does it take to have goals?
Larissa Albantakis
What does it take for a system, biological or not, to have goals? Here, this question is approached in the context of in silico artificial evolution. By examining the informational…
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…