• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.20-25
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• 2002

This paper presents a genetic programming based evolutionary strategy for on-line adaptive learnable evolvable hardware. Genetic programming can be useful control method for evolvable hardware for its unique tree structured chromosome. However it is difficult to represent tree structured chromosome on hardware, and it is difficult to use crossover operator on hardware. Therefore, genetic programming is not so popular as genetic algorithms in evolvable hardware community in spite of its possible strength. We propose a chromosome representation methods and a hardware implementation method that can be helpful to this situation. Our method uses context switchable identical block structure to implement genetic tree on evolvable hardware. We composed an evolutionary strategy for evolvable hardware by combining proposed method with other's striking research results. Proposed method is applied to the autonomous mobile robots cooperation problem to verify its usefulness.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.254-254
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• 2000

This paper presents a genetic programming based evolutionary strategy for on-line adaptive learnable evolvable hardware. genetic programming can be useful control method for evolvable hardware for its unique tree structured chromosome. However it is difficult to represent tree structured chromosome on hardware, and it is difficult to use crossover operator on hardware. Therefore, genetic programming is not so popular as genetic algorithms in evolvable hardware community in spite of its possible strength. We propose a chromosome representation methods and a hardware implementation method that can be helpful to this situation. Our method uses context switchable identical block structure to implement genetic tree on evolvable hardware. We composed an evolutionary strategy (or evolvable hardware by combining proposed method with other's striking research results. Proposed method is applied to the autonomous mobile robots cooperation problem to verify its usefulness.

• 전자공학회논문지 IE
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• v.45 no.4
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• pp.27-32
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• 2008

This paper presents the implementation of simple genetic algorithm using hardware description language for evolvable hardware embedded system. Evolvable hardware refers to hardware that can change its architecture and behavior dynamically and autonomously by interacting with its environment. So, it is especially suited to applications where no hardware specifications can be given in advance. Evolvable hardware is based on the idea of combining reconfigurable hardware device with evolutionary computation, such as genetic algorithm. Because of parallel, no function call overhead and pipelining, a hardware genetic algorithm give speedup over a software genetic algorithm. This paper suggests the hardware genetic algorithm for evolvable embedded system chip. That includes simulation results for several fitness functions.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.509-513
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• 2004

An area of research called evolvable hardware (EHW) has recently emerged which combines aspects of evolutionary computation with hardware design and synthesis. The features that can be used to identify and classify evolvable hardware are the evolutionary algorithm, the implementation and the genotype representation. This paper gives an introduction to the field. It continues by including classifying the EHW and the applications of the area.

• Journal of KIISE:Software and Applications
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• v.32 no.1
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• pp.62-73
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• 2005

Evolvable Hardware is the technique that obtains target function by adapting reconfigurable digital' devices to environment in real time using evolutionary computation. It opens the possibility of automatic design of hardware circuits but still has the limitation to produce complex circuits. In this paper, we have analyzed the fitness landscape of evolvable hardware and proposed a speciation technique of evolving diverse individuals simultaneously, proving the efficiency empirically. Also, we show that useful extra functions can be obtained by analyzing diverse circuits from the speciation technique.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.746-753
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• 2001

In this paper, we review the basic concept of Evolvable Hardware first. And we examine genetic algorithm processor and hardware reconfiguration method and implementation. By considering complexity and performance of hardware at the same time, we design genetic algorithm processor using modularization and parallel processing method. And we design frame that has connection structure and logic block on FPGA, and embody reconfigurable hardware that do so that this frame may be reconstructed by RAM. Also we implemented ECANS that information processing system such as living creatures'brain using this hardware reconfiguration method. And we apply ECANS which is implemented using the concept of Evolvable Hardware to time-series prediction problem in order to verify the effectiveness.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.449-450
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• 2007

Evolvable hardware(EHW) is a dynamic field that brings together reconfigurable hardware, artificial intelligence, fault tolerance and autonomous systems. This paper gives an introduction to the field. The features that can be used to identify and classify evolvable hardware are the evolutionary algorithm, the implementation and the genotype representation. Evolvable hardware (EHW) is hardware that can change its own circuit structure by genetic learning to achieve maximum adaptation to the environment. In conventional EHW, the learning is executed by software on a computer.

• 전자공학회논문지 IE
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• v.46 no.2
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• pp.7-10
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• 2009

This paper presents the implementation of libraries of hardware modules for genetic algorithm using VHDL. Evolvable hardware refers to hardware that can change its architecture and behavior dynamically and autonomously by interacting with its environment. So, it is especially suited to applications where no hardware specifications can be given in advance. Evolvable hardware is based on the idea of combining reconfigurable hardware device with evolutionary computation, such as genetic algorithm. Because of parallel, no function call overhead and pipelining, a hardware genetic algorithm give speedup over a software genetic algorithm. This paper suggests the hardware genetic algorithm for evolvable embedded system chip. That includes simulation results and analysis for several fitness functions. It can be seen that our design works well for the three examples.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1187-1188
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• 2008

An area of research called evolvable hardware has recently emerged which combines aspects of evolutionary computation with hardware design and synthesis. Evolvable hardware (EHW) is hardware that can change its own circuit structure by genetic learning to achieve maximum adaptation to the environment. In conventional EHW, the learning is executed by software on a computer. In this paper, we have studied and surveyed a gate-level evolvable hardware chip, by integrating both GA hardware and reconfigurable hardware within a single LSI chip. The chip consists of genetic algorithm(GA) hardware, reconfigurable hardware logic, and the control logic. In this paper, we describe the architecture, functions of the chip.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1364-1373
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• 2004

Recently Evolvable Hardware (EHW) is widely studied to design effective hardware circuits that can reconfigure themselves according to the environment. However, it is still difficult to apply for complicated circuits because the search space increases exponentially as the complexity of hardware increases. To remedy this problem, this paper proposes a method to evolve complex hardware with a modular approach. The comparative experiments of some digital circuits with the conventional evolutionary approach indicate that the proposed method yields from 50 times to 1,000 times faster evolution and more optimized hardware.