{"title":"Algorithmic Information Dynamics","authors":"H. Zenil, N. Kiani, Felipe S. Abrahão, J. Tegnér","doi":"10.4249/scholarpedia.53143","DOIUrl":"https://doi.org/10.4249/scholarpedia.53143","url":null,"abstract":"Biological systems are extensively studied as interactions forming complex networks. Reconstructing causal knowledge from, and principles of, these networks from noisy and incomplete data is a challenge in the field of systems biology. Based on an online course hosted by the Santa Fe Institute Complexity Explorer, this book introduces the field of Algorithmic Information Dynamics, a model-driven approach to the study and manipulation of dynamical systems . It draws tools from network and systems biology as well as information theory, complexity science and dynamical systems to study natural and artificial phenomena in software space. It consists of a theoretical and methodological framework to guide an exploration and generate computable candidate models able to explain complex phenomena in particular adaptable adaptive systems, making the book valuable for graduate students and researchers in a wide number of fields in science from physics to cell biology to cognitive sciences.","PeriodicalId":74760,"journal":{"name":"Scholarpedia journal","volume":"15 1","pages":"53143"},"PeriodicalIF":0.0,"publicationDate":"2020-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46541573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mathematical biology","authors":"F. Hoppensteadt","doi":"10.4249/scholarpedia.2877","DOIUrl":"https://doi.org/10.4249/scholarpedia.2877","url":null,"abstract":"This paper considers a model of the human cardiovascular-respiratory control system with one and two transport delays in the state equations describing the respiratory system. The effectiveness of the control of the ventilation rate V̇A is influenced by such transport delays because blood gases must be transported a physical distance from the lungs to the sensory sites where these gases are measured. The short term cardiovascular control system does not involve such transport delays although delays do arise in other contexts such as the baroreflex loop (see [46]) for example. This baroreflex delay is not considered here. The interaction between heart rate, blood pressure, cardiac output, and blood vessel resistance is quite complex and given the limited knowledge available of this interaction, we will model the cardiovascular control mechanism via an optimal control derived from control theory. This control will be stabilizing and is a reasonable approach based on mathematical considerations as well as being further motivated by the observation that many physiologists cite optimization as a potential influence in the evolution of biological systems (see, e.g., Kenner [29] or Swan [62]). In this paper we adapt a model, previously considered (Timischl [63] and Timischl et al. [64]), to include the effects of one and two transport delays. We will first implement an optimal control for the combined cardiovascular-respiratory model with one state space delay. We will then consider the effects of a second delay in the state space by modeling the respiratory control via an empirical formula with delay while the the complex relationships in the cardiovascular control will still be modeled by optimal control. This second transport delay associated with the sensory system of the respiratory control plays an important role in respiratory stability. As an application of this model we will consider congestive heart failure where this transport delay is larger than normal and the transition from the quiet awake state to stage 4 (NREM) sleep. The model can be used to study the interaction between cardiovascular and respiratory function in various situations as well as to consider the influence of optimal function in physiological control system performance. J.J. Batzel: SFB “Optimierung und Kontrolle”, Karl-Franzens-Universität, Heinrichstraße 22, 8010 Graz, Austria. e-mail: jerry.batzel@uni-graz.at F. Kappel: Institute for Mathematics and Scientific Computing and SFB “Optimierung und Kontrolle”, Karl-Franzens-Universität, Heinrichstraße 36, 8010 Graz, Austria. e-mail: franz.kappel@uni-graz.at S. Timischl-Teschl: Fachhochschule Technikum Wien, Hoechstaedplatz 5, 1200 Vienna, Austria. e-mail: susanne.teschl@technikum-wien.at Supported by FWF (Austria) under grant F310 as a subproject of the Special Research Center F003 “Optimization and Control” Mathematics Subject Classification (2000): 92C30, 49J15","PeriodicalId":74760,"journal":{"name":"Scholarpedia journal","volume":"52 1","pages":"2877"},"PeriodicalIF":0.0,"publicationDate":"2020-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70975077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Thornton, F. Hutchings, Richard J. Tomsett, Marcus Kaiser
{"title":"Vertex","authors":"C. Thornton, F. Hutchings, Richard J. Tomsett, Marcus Kaiser","doi":"10.4249/scholarpedia.53365","DOIUrl":"https://doi.org/10.4249/scholarpedia.53365","url":null,"abstract":"","PeriodicalId":74760,"journal":{"name":"Scholarpedia journal","volume":"29 1","pages":"53365"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70988892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reinforcement learning","authors":"F. Wörgötter, B. Porr","doi":"10.4249/scholarpedia.1448","DOIUrl":"https://doi.org/10.4249/scholarpedia.1448","url":null,"abstract":"The discussion here considers a much more common learning condition where an agent, such as a human or a robot, has to learn to make decisions in the environment from simple feedback. Such feedback is provided only after periods of actions in the form of reward or punishment without detailing which of the actions has contributed to the outcome. This type of learning scenario is called reinforcement learning. This learning problem is formalized in a Markov decision-making process with a variety of related algorithms. The second part of this chapter will use function approximators with neural networks which have made recent progress as deep reinforcement learning.","PeriodicalId":74760,"journal":{"name":"Scholarpedia journal","volume":"3 1","pages":"1448"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70967034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Schematic framework for theories of perception","authors":"E. Ahissar, Guy Nelinger, L. Gruber","doi":"10.4249/SCHOLARPEDIA.52463","DOIUrl":"https://doi.org/10.4249/SCHOLARPEDIA.52463","url":null,"abstract":"","PeriodicalId":74760,"journal":{"name":"Scholarpedia journal","volume":"14 1","pages":"52463"},"PeriodicalIF":0.0,"publicationDate":"2019-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48002225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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