scholarly journals A Probabilistic Approach to Control of Complex Systems and Its Application to Real-Time Pricing

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Koichi Kobayashi ◽  
Kunihiko Hiraishi
Keyword(s):  
Complex Systems ◽  
Real Time ◽  
Structural Control ◽  
Regulatory Networks ◽  
Control Method ◽  
Probabilistic Approach ◽  
Gene Regulatory ◽  
Real Time Pricing ◽  
Electricity Conservation ◽  
Approximate Solution Method

Control of complex systems is one of the fundamental problems in control theory. In this paper, a control method for complex systems modeled by a probabilistic Boolean network (PBN) is studied. A PBN is widely used as a model of complex systems such as gene regulatory networks. For a PBN, the structural control problem is newly formulated. In this problem, a discrete probability distribution appeared in a PBN is controlled by the continuous-valued input. For this problem, an approximate solution method using a matrix-based representation for a PBN is proposed. Then, the problem is approximated by a linear programming problem. Furthermore, the proposed method is applied to design of real-time pricing systems of electricity. Electricity conservation is achieved by appropriately determining the electricity price over time. The effectiveness of the proposed method is presented by a numerical example on real-time pricing systems.

scholarly journals A Fast and Effective Method to Identify Relevant Sets of Variables in Complex Systems

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1022
Author(s):  
Gianluca D’Addese ◽  
Martina Casari ◽  
Roberto Serra ◽  
Marco Villani
Keyword(s):  
Complex Systems ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Computational Cost ◽  
Graph Analysis ◽  
The Past ◽  
Medium Level ◽  
Micro Level ◽  
Gene Regulatory ◽  
High Level

In many complex systems one observes the formation of medium-level structures, whose detection could allow a high-level description of the dynamical organization of the system itself, and thus to its better understanding. We have developed in the past a powerful method to achieve this goal, which however requires a heavy computational cost in several real-world cases. In this work we introduce a modified version of our approach, which reduces the computational burden. The design of the new algorithm allowed the realization of an original suite of methods able to work simultaneously at the micro level (that of the binary relationships of the single variables) and at meso level (the identification of dynamically relevant groups). We apply this suite to a particularly relevant case, in which we look for the dynamic organization of a gene regulatory network when it is subject to knock-outs. The approach combines information theory, graph analysis, and an iterated sieving algorithm in order to describe rather complex situations. Its application allowed to derive some general observations on the dynamical organization of gene regulatory networks, and to observe interesting characteristics in an experimental case.

scholarly journals Macroscopic dynamics of gene regulatory networks revealed by individual entropy

2021 ◽  
Author(s):  
Cong Liu ◽  
Lijie Hao ◽  
Jinzhi Lei
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Temporal Dynamics ◽  
Transition Process ◽  
Network Structures ◽  
Structure Variation ◽  
Macroscopic Variable ◽  
Gene Regulatory

Complex systems are usually high-dimensional with intricate interactions among internal components, and may display complicated dynamics under different conditions. While it is difficult to measure detailed dynamics of each component, proper macroscopic description of a complex system is crucial for quantitative studies. In biological systems, each cell is a complex system containing a huge number of molecular components that are interconnected with each other through intricate molecular interaction networks. Here, we consider gene regulatory networks in a cell, and introduce individual entropy as a macroscopic variable to quantify the transcriptional dynamics in response to changes in random perturbations and/or network structures. The proposed individual entropy measures the information entropy of a system at each instant with respect to a basal reference state, and may provide temporal dynamics to characterize switches of system states. Individual entropy provides a method to quantify the stationary macroscopic dynamics of a gene set that is dependent on the gene regulation connections, and can be served as an indicator for the evolution of network structure variation. Moreover, the individual entropy with reference to a preceding state enables us to characterize different dynamic patterns generated from varying network structures. Our results show that the proposed individual entropy can be a valuable macroscopic variable of complex systems in characterizing the transition processes from order to disorder dynamics, and to identify the critical events during the transition process.

Evolution Towards Criticality in Ising Neural Agents

2020 ◽  
Vol 26 (1) ◽  
pp. 112-129 ◽  
Author(s):  
Sina Khajehabdollahi ◽  
Olaf Witkowski
Keyword(s):  
Complex Systems ◽  
Critical State ◽  
Regulatory Networks ◽  
Evolutionary Dynamics ◽  
Subcritical State ◽  
Experimental Conditions ◽  
Supercritical Regime ◽  
Gene Regulatory ◽  
Human Brains ◽  
Clear Description

Criticality is thought to be crucial for complex systems to adapt at the boundary between regimes with different dynamics, where the system may transition from one phase to another. Numerous systems, from sandpiles to gene regulatory networks to swarms to human brains, seem to work towards preserving a precarious balance right at their critical point. Understanding criticality therefore seems strongly related to a broad, fundamental theory for the physics of life as it could be, which still lacks a clear description of how life can arise and maintain itself in complex systems. In order to investigate this crucial question, we model populations of Ising agents competing for resources in a simple 2D environment subject to an evolutionary algorithm. We then compare its evolutionary dynamics under different experimental conditions. We demonstrate the utility that arises at a critical state and contrast it with the behaviors and dynamics that arise far from criticality. The results show compelling evidence that not only is a critical state remarkable in its ability to adapt and find solutions to the environment, but the evolving parameters in the agents tend to flow towards criticality if starting from a supercritical regime. We present simulations showing that a system in a supercritical state will tend to self-organize towards criticality, in contrast to a subcritical state, which remains subcritical though it is still capable of adapting and increasing its fitness.

Stationary and structural control in gene regulatory networks: basic concepts

2010 ◽  
Vol 41 (1) ◽  
pp. 5-16 ◽  
Author(s):  
Edward R. Dougherty ◽  
Ranadip Pal ◽  
Xiaoning Qian ◽  
Michael L. Bittner ◽  
Aniruddha Datta
Keyword(s):  
Gene Regulatory Networks ◽  
Structural Control ◽  
Regulatory Networks ◽  
Gene Regulatory ◽  
Basic Concepts

A Study on Real-Time Pricing Method of Reactive Power in Voltage Profile Control Method of Future Distribution Network

2012 ◽  
Vol 132 (4) ◽  
pp. 359-370 ◽  
Author(s):  
Akira Koide ◽  
Takao Tsuji ◽  
Tsutomu Oyama ◽  
Takuhei Hashiguchi ◽  
Tadahiro Goda ◽  
...  
Keyword(s):  
Real Time ◽  
Reactive Power ◽  
Control Method ◽  
Distribution Network ◽  
Voltage Profile ◽  
Profile Control ◽  
Real Time Pricing

scholarly journals Optimal Control of Probabilistic Logic Networks and Its Application to Real-Time Pricing of Electricity

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Koichi Kobayashi ◽  
Kunihiko Hiraishi
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Discrete Model ◽  
Large Scale ◽  
Mixed Integer ◽  
Probabilistic Logic ◽  
Integer Linear Programming Problem ◽  
Real Time Pricing ◽  
Electricity Conservation ◽  
Logic Functions

In analysis and control of large-scale complex systems, a discrete model plays an important role. In this paper, a probabilistic logic network (PLN) is considered as a discrete model. A PLN is a mathematical model where multivalued logic functions are randomly switched. For a PLN with two kinds of control inputs, the optimal control problem is formulated, and an approximate solution method for this problem is proposed. In the proposed method, using a matrix-based representation for a PLN, this problem is approximated by a mixed integer linear programming problem. In application, real-time pricing of electricity is studied. In real-time pricing, electricity conservation is achieved by setting a high electricity price. A numerical example is presented to show the effectiveness of the proposed method.

scholarly journals Macroscopic dynamics of gene regulatory networks revealed by individual entropy

2021 ◽  
Author(s):  
Cong Liu ◽  
Lijie Hao ◽  
Jinzhi Lei
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Temporal Dynamics ◽  
Transition Process ◽  
Network Structures ◽  
Structure Variation ◽  
Macroscopic Variable ◽  
Gene Regulatory

Complex systems are usually high-dimensional with intricate interactions among internal components, and may display complicated dynamics under different conditions. While it is {difficult} to measure detail dynamics of each component, proper macroscopic description of a complex system is crucial for quantitative studies. In biological systems, each cell is a complex system containing a huge number of molecular components that are interconnected with each other through intricate molecular interaction networks. Here, we consider gene regulatory networks in a cell, and introduce individual entropy as a macroscopic variable to quantify the transcriptional dynamics in response to changes in random perturbations and/or network structures. The proposed individual entropy measures the information entropy of a system at each instant with respect to a basal reference state, and may provide temporal dynamics to characterize switches of system states. Individual entropy provides a method to quantify the stationary macroscopic dynamics of a gene set that is dependent on the gene regulation connections, and can be served as an indicator for the evolution of network structure variation. Moreover, the individual entropy with reference to a preceding state enable us to characterize different dynamic patterns generated from varying network structures. Our results show that the proposed individual entropy can be a valuable macroscopic variable of complex systems in characterizing the transition processes from order to disorder dynamics, and to identify the critical events during the transition process.

scholarly journals Real-time in silico experiments on gene regulatory networks and surgery simulation on handheld devices

2014 ◽  
Vol 1 (1) ◽  
pp. 1 ◽  
Author(s):  
Icíar Alfaro ◽  
David González ◽  
Felipe Bordeu ◽  
Adrien Leygue ◽  
Amine Ammar ◽  
...  
Keyword(s):  
Real Time ◽  
Gene Regulatory Networks ◽  
In Silico ◽  
Regulatory Networks ◽  
Handheld Devices ◽  
Surgery Simulation ◽  
Gene Regulatory
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