The evolved radio and its implications for modelling the evolution of novel sensors

Bird, Jon; Layzell, P.

doi:10.1109/cec.2002.1004522

Cited by 34 publications

(29 citation statements)

References 9 publications

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“…Other times, the results are less desirable. For example, [8] used an evolutionary algorithm to optimise circuit design of a radio controller. Surprisingly, the optimal design found by the algorithm did not contain any oscillator, a component typically required.…”

Section: Predicting and Controlling Behaviourmentioning

confidence: 99%

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Universal Artificial Intelligence

Hutter

2018

Foundations of Trusted Autonomy

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Artificial intelligence (AI) bears the promise of making us all healthier, wealthier, and happier by reducing the need for human labour and by vastly increasing our scientific and technological progress.Since the inception of the AI research field in the mid-twentieth century, a range of practical and theoretical approaches have been investigated. This chapter will discuss universal artificial intelligence (UAI) as a unifying framework and foundational theory for many (most?) of these approaches. The development of a foundational theory has been pivotal for many other research fields. Well-known examples include the development of Zermelo-Fraenkel set theory (ZFC) for mathematics, Turingmachines for computer science, evolution for biology, and decision and game theory for economics and the social sciences. Successful foundational theories give a precise, coherent understanding of the field, and offer a common language for communicating research. As most research studies focus on one narrow question, it is essential that the value of each isolated result can be appreciated in light of a broader framework or goal formulation. UAI offers several benefits to AI research beyond the general advantages of foundational theories just mentioned. Substantial attention has recently been called to the safety of autonomous AI systems [10]. A highly intelligent autonomous system may cause substantial unintended harm if constructed carelessly. The trustworthiness of autonomous agents may be much improved if their design is grounded in a formal theory (such as UAI) that allows formal verification of their behavioural properties. Unsafe designs can be ruled out at an early stage, and adequate attention can be given to crucial design choices.

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Section: Predicting and Controlling Behaviourmentioning

confidence: 99%

“…The reason that it affects behaviour in UAI is that M is a semi-measure and not a measure. 8 These different kinds of agents have implications for AI safety. In Sect.…”

Section: Death and Self-preservationmentioning

confidence: 99%

Universal Artificial Intelligence

Hutter

2018

Foundations of Trusted Autonomy

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“…may have many local extrema or discontinuities [14]. Another quality which is extremely valuable is that the GAs are very efficient in terms of solving multivariable problems [15].…”

Section: Genetic Algorithmmentioning

confidence: 99%

An Efficient Method of Group Delay Equalization for Digital IIR Filters

Okoniewski¹,

Piskorowski²

2013

Metrology and Measurement Systems

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The paper presents the equalization problem of non-linear phase response of digital IIR type filters. An improved analytical method of designing a low-order equalizer is presented. The proposed approach is compared with the original method. The genetic algorithm is presented as an iterative method of optimization. The vector and matrix representation of the all-pass equalizer are shown and introduced to the algorithm. The results are compared with the analytical method. In this paper we have also proposed the use of an aging factor and setting the initial population of the genetic algorithm around the solution provided by the analytical methodology.

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“…Finally, the surprising work of Bird and Layzell [4] has also demonstrated the evolution of an antenna design, albeit by accident. In their experiment to evolve an electronic circuit that produced an oscillating signal as output, they discovered that instead, evolution had produced a primitive receiver that was receiving the background noise created by a nearby computer monitor and modifying it.…”

Section: Evolutionary Antennasmentioning

confidence: 99%

Innately adaptive robotics through embodied evolution

Mahdavi

Bentley

2006

Auton Robot

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-Autonomous adaptation in robots has become recognised as crucial for devices deployed in remote or inhospitable environments. The aim of this work is to investigate autonomous robot adaptation, focussing on damage recovery and adaptation to unknown environments. An embodied evolutionary algorithm is introduced and its capabilities demonstrated with experimental results. This algorithm is shown to be able to control the motion of a robot snake effectively; this same algorithm inherently recovers the snake's motion after damage. Another experiment shows that the algorithm is capable of contorting a shape-changing antenna in such a way as to minimise the affect of background noise on it, thus allowing the antenna to achieve a better signal.

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The evolved radio and its implications for modelling the evolution of novel sensors

Cited by 34 publications

References 9 publications

Universal Artificial Intelligence

Universal Artificial Intelligence

An Efficient Method of Group Delay Equalization for Digital IIR Filters

Innately adaptive robotics through embodied evolution

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