scholarly journals Evaluating Approximations and Heuristic Measures of Integrated Information

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 525 ◽  
Author(s):  
André Sevenius Nilsen ◽  
Bjørn Erik Juel ◽  
William Marshall
Keyword(s):  
Binary Systems ◽  
Initial Conditions ◽  
Transition Probability ◽  
Ground Truth ◽  
Transition Probability Matrix ◽  
Efficient Estimation ◽  
Model Systems ◽  
Practical Applications ◽  
Linear Threshold ◽  
Integrated Information

Integrated information theory (IIT) proposes a measure of integrated information, termed Phi (Φ), to capture the level of consciousness of a physical system in a given state. Unfortunately, calculating Φ itself is currently possible only for very small model systems and far from computable for the kinds of system typically associated with consciousness (brains). Here, we considered several proposed heuristic measures and computational approximations, some of which can be applied to larger systems, and tested if they correlate well with Φ. While these measures and approximations capture intuitions underlying IIT and some have had success in practical applications, it has not been shown that they actually quantify the type of integrated information specified by the latest version of IIT and, thus, whether they can be used to test the theory. In this study, we evaluated these approximations and heuristic measures considering how well they estimated the Φ values of model systems and not on the basis of practical or clinical considerations. To do this, we simulated networks consisting of 3–6 binary linear threshold nodes randomly connected with excitatory and inhibitory connections. For each system, we then constructed the system’s state transition probability matrix (TPM) and generated observed data over time from all possible initial conditions. We then calculated Φ, approximations to Φ, and measures based on state differentiation, coalition entropy, state uniqueness, and integrated information. Our findings suggest that Φ can be approximated closely in small binary systems by using one or more of the readily available approximations (r > 0.95) but without major reductions in computational demands. Furthermore, the maximum value of Φ across states (a state-independent quantity) correlated strongly with measures of signal complexity (LZ, rs = 0.722), decoder-based integrated information (Φ*, rs = 0.816), and state differentiation (D1, rs = 0.827). These measures could allow for the efficient estimation of a system’s capacity for high Φ or function as accurate predictors of low- (but not high-)Φ systems. While it is uncertain whether the results extend to larger systems or systems with other dynamics, we stress the importance that measures aimed at being practical alternatives to Φ be, at a minimum, rigorously tested in an environment where the ground truth can be established.

scholarly journals Evaluating Approximations and Heuristic Measures of Integrated Information

2019 ◽  
Author(s):  
André Sevenius Nilsen ◽  
Bjørn Erik Juel ◽  
William Marshall ◽  
Johan Frederik Storm
Keyword(s):  
Binary Systems ◽  
State Transition ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Efficient Estimation ◽  
Model Systems ◽  
System Level ◽  
Independent Manner ◽  
Practical Applications ◽  
Integrated Information

Integrated information theory (IIT) proposes a measure of integrated information (Φ) to capture the level of consciousness for a physical system in a given state. Unfortunately, calculating Φ itself is currently only possible for very small model systems, and far from computable for the kinds of systems typically associated with consciousness (brains). Here, we consider several proposed measures and computational approximations, some of which can be applied to larger systems, and test if they correlate well with Φ. While these measures and approximations capture intuitions underlying IIT and some have had success in practical applications, it has not been shown that they actually quantify the type of integrated information specified by the latest version of IIT. In this study, we evaluated these approximations and heuristic measures, based not on practical or clinical considerations, but rather based on how well they estimate the Φ values of model systems. To do this, we simulated networks consisting of 3–6 binary linear threshold nodes randomly connected with excitatory and inhibitory connections. For each system, we then constructed the system’s state transition probability matrix (TPM), as well as its state transition matrix (STM) over time for all possible initial states. From these matrices, we calculated, approximations to Φ, and measures based on state differentiation, state entropy, state uniqueness, and integrated information. All measures were correlated with Φ in a state dependent and state independent manner. Our findings suggest that Φ can be approximated closely in small binary systems by using one or more of the readily available approximations (r > 0.95), but without major reductions in computational demands. Furthermore, Φ correlated strongly with measures of signal complexity (LZ, rs = 0.722), decoder based integrated information (Φ*, rs = 0.816), and state differentiation (D1, rs = 0.827), on the system level (state independent). These measures could allow for efficient estimation of Φ on a group level, or as accurate predictors of low, but not high, Φ systems. While it’s uncertain whether the results extend to larger systems or systems with other dynamics, we stress the importance that measures aimed at being practical alternatives to Φ are at a minimum rigorously tested in an environment where the ground truth can be established.

Particle motion with air resistance

2012 ◽  
Vol 8 (1) ◽  
pp. 1-15
Author(s):  
Gy. Sitkei
Keyword(s):  
Basic Equation ◽  
Initial Conditions ◽  
Equation Of Motion ◽  
Terminal Velocity ◽  
Dimensionless Form ◽  
Wood Industry ◽  
Acceptable Error ◽  
General Validity ◽  
Practical Applications ◽  
Air Resistance

Motion of particles with air resistance (e.g. horizontal and inclined throwing) plays an important role in many technological processes in agriculture, wood industry and several other fields. Although, the basic equation of motion of this problem is well known, however, the solutions for practical applications are not sufficient. In this article working diagrams were developed for quick estimation of the throwing distance and the terminal velocity. Approximate solution procedures are presented in closed form with acceptable error. The working diagrams provide with arbitrary initial conditions in dimensionless form of general validity.

On calculating extinction probabilities for branching processes in random environments

1969 ◽  
Vol 6 (03) ◽  
pp. 478-492 ◽  
Author(s):  
William E. Wilkinson
Keyword(s):  
Generating Functions ◽  
Infinite Sequence ◽  
Branching Processes ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Random Environments ◽  
Real Numbers ◽  
Discrete Time Markov Chain ◽  
Extinction Probabilities ◽  
Image Position

Consider a discrete time Markov chain {Zn } whose state space is the non-negative integers and whose transition probability matrix ║Pij ║ possesses the representation where {Pr }, r = 1,2,…, is a finite or denumerably infinite sequence of non-negative real numbers satisfying , and , is a corresponding sequence of probability generating functions. It is assumed that Z 0 = k, a finite positive integer.

Further enhancement on H∞ sliding mode control design for singular Markovian jump systems with partly known transition probabilities

2021 ◽  
pp. 107754632198920
Author(s):  
Zeinab Fallah ◽  
Mahdi Baradarannia ◽  
Hamed Kharrati ◽  
Farzad Hashemzadeh
Keyword(s):  
Transition Probabilities ◽  
Sliding Mode ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Linear Matrix ◽  
Sliding Mode Controller ◽  
Sliding Surface ◽  
Markovian Jump ◽  
Markovian Jump System ◽  
Singular Markovian Jump Systems

This study considers the designing of the H ∞ sliding mode controller for a singular Markovian jump system described by discrete-time state-space realization. The system under investigation is subject to both matched and mismatched external disturbances, and the transition probability matrix of the underlying Markov chain is considered to be partly available. A new sufficient condition is developed in terms of linear matrix inequalities to determine the mode-dependent parameter of the proposed quasi-sliding surface such that the stochastic admissibility with a prescribed H ∞ performance of the sliding mode dynamics is guaranteed. Furthermore, the sliding mode controller is designed to assure that the state trajectories of the system will be driven onto the quasi-sliding surface and remain in there afterward. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design algorithms.

scholarly journals Defining the Binary Star Population in the Young Open Cluster M35 (NGC 2168)

2007 ◽  
Vol 3 (S246) ◽  
pp. 105-106
Author(s):  
Ella K. Braden ◽  
Robert D. Mathieu ◽  
Sören Meibom
Keyword(s):  
Binary Systems ◽  
Initial Conditions ◽  
Binary Star ◽  
Open Cluster ◽  
Open Clusters ◽  
Spatial Period ◽  
Large Sample Size ◽  
Long Baseline ◽  
Dynamical Simulations ◽  
Young Open Cluster

AbstractWe present current results from the ongoing WIYN Open Cluster Study radial-velocity survey for 1410 stars in the young (150 Myr) open cluster M35 (NGC 2168) and establish a benchmark for initial conditions in young open clusters. We find for periods ≲ 1000 days a minimum binary frequency of 0.36 – 0.51. We also analyze the spatial, period and eccentricity distributions of the binary systems and find that the period and eccentricity distributions are well approximated by scaled field distributions from Duquennoy & Mayor (1991). With our large sample size and long baseline, we have a unique understanding of the binary population in this young cluster, making it ideal for defining initial conditions for dynamical simulations.

Exploring the dust ring in the circum-binary disc around GG Tau A

2021 ◽  
Author(s):  
Claudia Toci ◽  
Simone Ceppi ◽  
Nicolas Cuello ◽  
Giuseppe Lodato ◽  
Cristiano Longarini ◽  
...  
Keyword(s):  
Binary Systems ◽  
Planet Formation ◽  
Initial Conditions ◽  
Scattered Light ◽  
Complex Structure ◽  
Semimajor Axis ◽  
Continuum Emission ◽  
Orbital Parameter ◽  
Semi Major Axis ◽  
Multiple Systems

<p>Binaries and multiple systems are common among young stars (Reipurth et al. 2014). These stars are often surrounded by discs of gas and dust, formed due to the conservation of angular momentum of the collapsing cloud, thought to be the site of planet formation.<br />In the case of binary systems, three discs can form: an outer disc surrounding all the stars (called circumbinary disc), and two inner discs around the stars. As circumbinary planets have recently been discovered by Kepler (see e.g., Martin 2018, Bonavita & Desidera 2020), it is crucial to understand the dynamics and evolution of circumbinary discs to better understand the initial conditions of planet formation in multiple systems.<br />The GG Tau A system is an example of a young multiple T Tauri star. The binary is surrounded by a bright disc, observed in the continuum emission at different wavelengths (see e.g., Guilloteau et al. 1999; Dutrey et al. 2014; Phuong et al. 2020b) and in scattered light (e.g., Duchene et al. 2014, Keppler et al. 2020). The disc extends in the dust from 180 to 280 au from the center of mass, and in the gas up to 850 au. The inner (<180 au) part is depleted in gas and dust. Scattered light images show a complex structure in the inner part of the disc, with arcs and filamentary structures connecting the outer ring with the arcs and three shadows.<br />Two different configurations are possible fitting the proper motion data for the system: a co-planar case with a low eccentricity binary with a semi-major axis of 34 au, explored by Cazzoletti et al. 2017 and Keppler et al. 2020, and a misaligned case (i=30) with an eccentric binary (e=0.45) and a wider semimajor axis of 60 au (Aly et al.2018). At the state of the art, all these analyses focused on the gas dynamics only.<br />We will show the results of new 3D SPH simulations of dust and gas performed with the code PHANTOM, devised to test the two possible scenarios. We will describe the dynamics of the system in the two cases, comparing our models with observational results in order to better constraint the orbital parameter of the GG Tau A system. Our predictions will guide future observing campaigns and shed light on the complex evolution of discs in triple stellar systems.</p> <p> </p>

Asynchronous quadratic control for constrained hidden markov jump linear systems with incomplete MTPM and MOCPM

2021 ◽  
Author(s):  
Jin Zhu ◽  
Kai Xia ◽  
Geir E Dullerud
Keyword(s):  
Linear Systems ◽  
Controller Design ◽  
Hidden Markov ◽  
Transition Probability ◽  
Original System ◽  
Transition Probability Matrix ◽  
Markov Jump ◽  
Jump Linear Systems ◽  
Weighting Matrix ◽  
Markov Jump Linear Systems

Abstract This paper investigates the quadratic optimal control problem for constrained Markov jump linear systems with incomplete mode transition probability matrix (MTPM). Considering original system mode is not accessible, observed mode is utilized for asynchronous controller design where mode observation conditional probability matrix (MOCPM), which characterizes the emission between original modes and observed modes is assumed to be partially known. An LMI optimization problem is formulated for such constrained hidden Markov jump linear systems with incomplete MTPM and MOCPM. Based on this, a feasible state-feedback controller can be designed with the application of free-connection weighting matrix method. The desired controller, dependent on observed mode, is an asynchronous one which can minimize the upper bound of quadratic cost and satisfy restrictions on system states and control variables. Furthermore, clustering observation where observed modes recast into several clusters, is explored for simplifying the computational complexity. Numerical examples are provided to illustrate the validity.

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