I ?rst met Jingqiao when he had just commenced his PhD research in evolutionary algorithms with Arthur Sanderson at Rensselaer. Jingqiao's goals then were the investigation and development of a novel class of se- adaptivedi?erentialevolutionalgorithms, later calledJADE. I had remarked to Jingqiao then that Arthur always appreciated strong theoretical foun- tions in his research, so Jingqiao's prior mathematically rigorous work in communications systems would be very useful experience. Later in 2007, whenJingqiaohadcompletedmostofthetheoreticalandinitialexperimental work on JADE, I invited him to spend a year at GE Global Research where he applied his developments to several interesting and important real-world problems. Most evolutionary algorithm conferences usually have their share of in- vative algorithm oriented papers which seek to best the state of the art - gorithms. The best algorithms of a time-frame create a foundation for a new generationof innovativealgorithms, and so on, fostering a meta-evolutionary search for superior evolutionary algorithms. In the past two decades, during whichinterest andresearchin evolutionaryalgorithmshavegrownworldwide by leaps and bounds, engaging the curiosity of researchers and practitioners frommanydiversescienceandtechnologycommunities, developingstand-out algorithms is getting progressively harder.

Robotic systems are characterized by the intersection of computer intelligence with the physical world. This blend of physical reasoning and computational intelligence is well illustrated by the Tetrobot study described in this book. Tetrobot: A Modular Approach to Reconfigurable Parallel Robotics describes a new approach to the design of robotic systems. The Tetrobot approach utilizes modular components which may be reconfigured into many different mechanisms which are suited to different applications. The Tetrobot system includes two unique contributions: a new mechanism (a multilink spherical joint design), and a new control architecture based on propagation of kinematic solutions through the structure. The resulting Tetrobot system consists of fundamental components which may be mechanically reassembled into any modular configuration, and the control architecture will provide position control of the resulting structure. A prototype Tetrobot system has been built and evaluated experimentally. Tetrobot arms, platforms, and walking machines have been built and controlled in a variety of motion and loading conditions. The Tetrobot system has applications in a variety of domains where reconfiguration, flexibility, load capacity, and failure recovery are important aspects of the task. A number of key research directions have been opened by the Tetrobot research activities. Continuing topics of interest include: development of a more distributed implementation of the computer control architecture, analysis of the dynamics of the Tetrobot system motion for improved control of high-speed motions, integration of sensor systems to control the motion and shape of the high-dimensionality systems, and exploration of self-reconfiguration of the system. Tetrobot: A Modular Approach to Reconfigurable Parallel Robotics will be of interest to research workers, specialists and professionals in the areas of robotics, mechanical systems and computer engineering.

Robotic systems are characterized by the intersection of computer intelligence with the physical world. This blend of physical reasoning and computational intelligence is well illustrated by the Tetrobot study described in this book. Tetrobot: A Modular Approach to Reconfigurable Parallel Robotics describes a new approach to the design of robotic systems. The Tetrobot approach utilizes modular components which may be reconfigured into many different mechanisms which are suited to different applications. The Tetrobot system includes two unique contributions: a new mechanism (a multilink spherical joint design), and a new control architecture based on propagation of kinematic solutions through the structure. The resulting Tetrobot system consists of fundamental components which may be mechanically reassembled into any modular configuration, and the control architecture will provide position control of the resulting structure. A prototype Tetrobot system has been built and evaluated experimentally. Tetrobot arms, platforms, and walking machines have been built and controlled in a variety of motion and loading conditions. The Tetrobot system has applications in a variety of domains where reconfiguration, flexibility, load capacity, and failure recovery are important aspects of the task. A number of key research directions have been opened by the Tetrobot research activities. Continuing topics of interest include: development of a more distributed implementation of the computer control architecture, analysis of the dynamics of the Tetrobot system motion for improved control of high-speed motions, integration of sensor systems to control the motion and shape of the high-dimensionality systems, and exploration of self-reconfiguration of the system. Tetrobot: A Modular Approach to Reconfigurable Parallel Robotics will be of interest to research workers, specialists and professionals in the areas of robotics, mechanical systems and computer engineering.

I ?rst met Jingqiao when he had just commenced his PhD research in evolutionary algorithms with Arthur Sanderson at Rensselaer. Jingqiao's goals then were the investigation and development of a novel class of se- adaptivedi?erentialevolutionalgorithms, later calledJADE. I had remarked to Jingqiao then that Arthur always appreciated strong theoretical foun- tions in his research, so Jingqiao's prior mathematically rigorous work in communications systems would be very useful experience. Later in 2007, whenJingqiaohadcompletedmostofthetheoreticalandinitialexperimental work on JADE, I invited him to spend a year at GE Global Research where he applied his developments to several interesting and important real-world problems. Most evolutionary algorithm conferences usually have their share of in- vative algorithm oriented papers which seek to best the state of the art - gorithms. The best algorithms of a time-frame create a foundation for a new generationof innovativealgorithms, and so on, fostering a meta-evolutionary search for superior evolutionary algorithms. In the past two decades, during whichinterest andresearchin evolutionaryalgorithmshavegrownworldwide by leaps and bounds, engaging the curiosity of researchers and practitioners frommanydiversescienceandtechnologycommunities, developingstand-out algorithms is getting progressively harder.

This book describes an approach to intelligent task planning in a robotic system. Petri net and fuzzy logic are integrated and used to represent task sequence planning and error recovery. During the generation and execution of task plans, different kinds of uncertainties need to be handled to ensure the efficiency and reliability of the system. Following a systematic modeling procedure, a fuzzy Petri net is constructed based on geometric relations, fuzzy variables, and reasoning structures. The resulting net can be used to analyze and control the system. Many examples are discussed to illustrate the theory and the applications of fuzzy Petri nets.

In this book, efficient and scalable coevolutionary algorithms for distributed, network-based decision-making, which utilize objective functions are developed in a networked environment where internode communications are a primary factor in system performance. A theoretical foundation for this class of coevolutionary algorithms is introduced using techniques from stochastic process theory and mathematical analysis. A case study in distributed, network-based decision-making presents an implementation and detailed evaluation of the coevolutionary decision-making framework that incorporates distributed evolutionary agents and mobile agents. The methodology discussed in this book can have a fundamental impact on the principles and practice of engineering in the distributed, network-based environment that is emerging within and among corporate enterprise systems. In addition, the conceptual framework of the approach to distributed decision systems described may have much wider implications for network-based systems and applications.