State Space

#concept11 mentions

A state space (or, which is roughly equivalent, phase space) is the set of all possible states of a Dynamical System; each state of the system corresponds to a unique point in the state space.

Describing a system in its state space means switching from a simple space (with 3 dimensions) and complex things (made out of N elements) to a complex space (3^N dimensions) and simple things (points in that space).

A system’s development over time, i.e. its System Dynamics is equivalent to a trajectory in its state space. All possible trajectories in the space can be expressed as vectors; their aggregation is called the phase portrait of the state space.

The regions of the state space in which a system stays or to which it returns (i.e. in which it is stable) are the system’s Attractor regions.

An Attractor Landscape is the abstraction of a state space to what is relevant, i.e. interesting to us – attractors and possible trajectories between them.

References

Attractor Landscape

An attractor landscape is an abstraction of the State Space of a System.

Attractor

An attractor is the set of states a System tends to be in given what it is or how it can maintain its boundaries.

Causation

We want to Use a parsimonious and productive ontology in which modality is dissolved into systems described in State Spaces: there are no more basic principles of change and modality beyond … local constraints; they, and not possible worlds, laws, or counterfactuals, are the ontological bedrock of dynamical organization.

Complex System

A complex system is a Dynamical System that has the following attributes:Derived from Mitchell (2009) and Ladyman & Wiesner (2020).

Constraint

Constraints are relational properties components acquire in virtue of being embedded in a higher level SystemJuarrero (1998), 234 alterations in the probability distribution of a system’s State Spaceibid.

Dynamical System

A dynamical system is a System that changes over time.

Prioritise Abstraction Over Metaphor

Usually, the Abstractions we are using are based on Conceptual Metaphors.

Scale Free Abstraction

Scale-free abstractions are a specific type of Shorthand Abstractions: highly general concepts taken from our best current thinking about evolution, cognition, and the world as a hierarchy of systems.

Systems Emerge Due to Constraints

Systems or, more precisely, dissipative and autocatalytic structures that are precursors of autonomous, e.

Systems Live in State Spaces

We should Use a parsimonious and productive ontology.

The World Is a Hierarchy of Systems

When thinking about ontology (put simply, what the world consists of), we can start with the basic fact that there is difference in the world – that “something can be distinguished from everything else”.