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检索条件"机构=Genetic Programming"

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Automatic computational discovery of chemical reaction networks using genetic programming

Automatic computational discovery of chemical reaction netwo...

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作者： Koza, John R. Mydlowec, William Lanza, Guido Yu, Jessen Keane, Martin A. Department of Medicine Biomedical Informatics Stanford University Stanford CA United States Genetic Programming Inc. Los Altos CA United States Econometrics Inc. Chicago IL United States

ISBN: (纸本)9783540739197

The concentrations of substances participating in networks of chemical reactions are often modeled by non-linear continuous-time differential equations. Recent work has demonstrated that genetic programming is capable of automatically creating complex networks (such as analog electrical circuits and controllers) whose behavior is modeled by linear and non-linear continuous-time differential equations and whose behavior matches prespecified output values. This chapter demonstrates that it is possible to automatically induce (reverse engineer) a network of chemical reactions from observed time-domain data. genetic programming starts with observed time-domain concentrations of substances and automatically creates both the topology of the network of chemical reactions and the rates of each reaction of a network such that the behavior of the automatically created network matches the observed time-domain data. Specifically, genetic programming automatically created a network of four chemical reactions that consume glycerol and fatty acid as input, use ATP as a cofactor, and produce diacyl-glycerol as the final product. The network was created from 270 data points. The topology and sizing of the entire network was automatically created using the time-domain concentration values of diacyl-glycerol (the final product). The automatically created network contains three key topological features, including an internal feedback loop, a bifurcation point where one substance is distributed to two different reactions, and an accumulation point where one substance is accumulated from two sources. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Natural sciences computing

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Automated re-invention of a previously patented optical lens system using genetic programming

Automated re-invention of a previously patented optical lens...

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8th European Conference on genetic programming, EuroGP 2005

作者： Al-Sakran, Sameer H. Koza, John R. Jones, Lee W. Genetic Programming Inc. Mountain View CA United States Stanford University Stanford CA United States

The three dozen or so known instances of human-competitive designs of antennas, mechanical systems, circuits, and controllers produced by genetic programming suggest the question of whether genetic programming can be extended to the design of complex structures from other fields. This paper describes how genetic programming can be used to automatically create a complete design for an optical lens system "from scratch" - without starting from a pre-existing good design and without pre-specifying the number of lenses, the layout of lenses, or the numerical parameters of the lenses. More particularly, genetic programming created an optical system that infringed a previous patent (the Konig patent) and improved upon another previous patent (the Tackaberry-Muller patent). The genetically evolved design is an example of a human-competitive result produced by genetic programming in the field of optical design. © Springer-Verlag Berlin Heidelberg 2005.

关键词： genetic algorithms

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Automated synthesis of both the topology and numerical parameters for seven patented optical lens systems using genetic programming

Automated synthesis of both the topology and numerical param...

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Current Developments in Lens Design and Optical Engineering VI

作者： Jones, Lee W. Al-Sakran, Sameer H. Koza, John R. Genetic Programming Inc. Mountain View CA 94041 United States Stanford University Stanford CA 94305 United States

This paper describes how genetic programming was used as an automated invention machine to synthesize both the topology and numerical parameters for seven previously patented optical lens systems, including one aspherical system and one issued in the 21st-century. Two of the evolved optical lens systems infringe the claims of the patents and the others are novel solutions that satisfy the design goals stated in the patent. The automatic synthesis was done "from scratch" - that is, without starting from a pre-existing good design and without pre-specifying the number of lenses, the topological layout of the lenses, or the numerical parameters of the lenses. genetic programming is a form of evolutionary computation used to automatically solve problems. It starts from a high-level statement of what needs to be done and progressively breeds a population of candidate individuals over many generations using the principle of Darwinian natural selection and genetic recombination. The paper describes how genetic programming created eyepieces that duplicated the functionality of seven previously patented lens systems. The seven designs were created in a substantially similar and routine way, suggesting that the use of genetic programming in the automated design of both the topology and numerical parameters for optical lens systems may have widespread utility.

关键词： Optical instrument lenses

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Cross-domain features of runs of genetic programming used to evolve designs for analog circuits, optical lens systems, controllers, antennas, mechanical systems, and quantum computing circuits

Cross-domain features of runs of genetic programming used to...

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NASA/DoD Workshop on Evolvable Hardware

作者： J.R. Koza S.H. Al-Sakran L.W. Jones University of Stanford Stanford CA USA Genetic Programming Inc. Mountain View CA USA

genetic programming has now been successfully used to automatically synthesize human-competitive designs in a number of fields, including analog electrical circuits, optical lens systems, antennas, controllers, mechanical systems, and quantum computing circuits. Despite considerable variation in representation and technique, the above results share a number of common features. This paper identifies five common features and suggests possible explanations and interpretations for them. Some of these cross-domain observations clearly could not have been anticipated prior to the work being done.

关键词： Optical control Quantum computing genetic programming Optical design Analog circuits Lenses Control systems Mechanical systems Quantum mechanics Analog computers

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The root causes of code growth in genetic programming

The root causes of code growth in genetic programming

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6th European Conference on genetic programming, EuroGP 2003

作者： Streeter, Matthew J. Genetic Programming Inc United States

ISBN: (纸本)354000971X

This paper discusses the underlying pressures responsible for code growth in genetic programming, and shows how an understanding of these pressures can be used to use to eliminate code growth while simultaneously improving performance. We begin with a discussion of two distinct components of code growth and the extent to which each component is relevant in practice. We then define the concept of resilience in GP trees, and show that the buildup of resilience is essential for code growth. We present simple modifications to the selection procedures used by GP that eliminate bloat without hurting performance. Finally, we show that eliminating bloat can improve the performance of genetic programming by a factor that increases as the problem is scaled in difficulty. © 2003, Springer-Verlag Berlin Heidelberg, All rights Reserved.

关键词： genetic programming

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Use of genetic programming for automatic synthesis of post-2000 patented analog electrical circuits and patentable controllers

Use of genetic programming for automatic synthesis of post-2...

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8th International Conference on Computer Aided Optimum Design of Structures

作者： Streeter, MJ Keane, MA Koza, JR Genetic Programming Inc. United States Econometrics Inc. United States Stanford University United States

ISBN: (纸本)1853129720

This paper describes how we used genetic programming to automatically create the design of both the structure (topology) and sizing (component values) of analog electrical circuits that duplicate the functionality of five post-2000 patented inventions. The paper also describes how we used genetic programming to automatically create the design of both the structure (topology) and tuning (parameter values) of a general-purpose controller that outperforms conventional controllers for industrially representative plants.

关键词： Networks (circuits)

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Automatic synthesis using genetic programming of both the topology and sizing for five post-2000 patented analog and mixed analog-digital circuits

Automatic synthesis using genetic programming of both the to...

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Southwest Symposium on Mixed-Signal Design (SSMSD)

作者： M.J. Streeter M.A. Keane J.R. Koza Genetic Programming Inc. Mountain View CA USA Econometrics Inc. Chicago IL USA University of Stanford Stanford CA USA

Recent work has demonstrated that genetic programming can automatically create both the topology (graphical structure) and sizing (numerical component values) for analog electrical circuits merely by specifying the circuit's high level behavior (e.g., its desired or observed output, given its input). This automatic synthesis of analog circuits is accomplished using only tools for the analysis of circuits (e.g., a circuit simulator) and without relying on any human know-how concerning the synthesis of circuits. This paper applies genetic programming to the automatic synthesis of five analog and mixed analog-digital circuits that duplicate the functionality of circuits patented after January 1, 2000. The five automatically created circuits read on some (but not all) of the elements of various claims of the patents involved (and therefore do not infringe). The described method can be used as an automated invention machine either to produce potentially patentable new circuits or to "engineer around" existing patents.

关键词： Circuit synthesis genetic programming Circuit topology Analog-digital conversion Analog circuits Biology computing Circuit analysis Analytical models Circuit simulation Humans

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Automatic synthesis using genetic programming of an improved general-purpose controller for industrially representative plants

Automatic synthesis using genetic programming of an improved...

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NASA/DoD Workshop on Evolvable Hardware

作者： M.A. Keane J.R. Koza M.J. Streeter Econometrics Inc. Chicago IL USA University of Stanford Stanford CA USA Genetic Programming Inc. Mountain View CA USA

Most real-world controllers are composed of proportional, integrative, and derivative Signal processing blocks. The so-called PID controller was invented and patented by A. Callender and A.B. Stevenson (1939). Later J.G. Ziegler and N.B. Nichols (1942) developed mathematical rules for automatically selecting the parameter values for PID controllers. In their influential book, K.J. Astrom and T. Hagglund (1995) developed a world-beating PID controller that outperforms the 1942 Ziegler-Nichols rules on an industrially representative set of plants. In this paper, we approached the problem of automatic synthesis of a controller using genetic programming without requiring in advance that the topology of the plant be the conventional PID topology. We present a genetically evolved controller that outperforms the automatic tuning rules developed by Astrom and Hagglund in 1995 for the industrially representative set of plants specified by Astrom and Hagglund.

关键词： genetic programming Automatic control Industrial control Three-term control Topology Signal synthesis PD control Proportional control Signal processing Books

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Routine high-return human-competitive evolvable hardware

Routine high-return human-competitive evolvable hardware

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Proceedings - 2004 NASA/DoD Conference on Evolvable Hardware

作者： Koza, John R. Keane, Martin A. Streeter, Matthew J. Stanford University Stanford CA Econometrics Inc. Chicago IL Genetic Programming Inc. Mountain View CA

ISBN: (纸本)0769521452

This paper reviews the use of genetic programming as an automated invention machine for the synthesis of both the topology and sizing of analog electrical circuits. The paper focuses on the importance of the developmental representation in this process. The paper makes the point that genetic programming now routinely delivers high-return human-competitive machine intelligence. It also makes the point that genetic programming has delivered a progression of qualitatively more substantial results in synchrony with five approximately order-of-magnitude increases in the expenditure of computer time. The paper shows six examples where genetic programming has synthesized a circuit that duplicates the functionality or infringes a 21st-century patented electrical circuit. Finally, the paper discusses how genetic programming can be enhanced in order to potentially enable it to deliver more complex industrial-strength results.

关键词： Networks (circuits)

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Routine high-return human-competitive evolvable hardware

Routine high-return human-competitive evolvable hardware

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NASA/DoD Workshop on Evolvable Hardware

作者： J.R. Koza M.A. Keane M.J. Streeter University of Stanford Stanford CA USA Econometrics Inc. Chicago IL USA Genetic Programming Inc. Mountain View CA USA

关键词： Hardware genetic programming Circuit synthesis Circuit topology Machine intelligence Biology computing Resistors Capacitors Electric variables measurement Size measurement

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