A Pipe Route System Design Methodology for the Representation of Imaginal Thinking
Yuehong Yin, Chen Zhou, Hao Che · Advances in Knowledge Representation · 2012
Human beings have long been fascinated by figuring out the accurate answer to what the essential characteristic of human thinking really is.Besides, how knowledge is represented in human mind is also a mystery.However, limitations of development of traditional Artificial Intelligence framing of human thinking: logical thinking and intuitive thinking have deterred this process.Furthermore, such traditional AI framing has been challenged by Brooks' actionbased AI theory with nontraditional symbolic representations and reasoning.Radically different from the above traditional views, we consider thinking in terms of images is the fundamental characteristics of human thinking and memory and knowledge are all stored as high dimensional images.Thereby we define this kind of thinking style as imaginal thinking.Humans often think by forming images based on experience or knowledge and comparing them holistically and directly.Experimental psychologists have also shown that people actually use images, not descriptions as computers do, to understand and respond to some situations.This process is quite different from the logical, step-by-step accurate massive computation operations in a framed world that computers can perform.We argue that logical thinking and intuitive thinking are partial understanding to human thinking in AI research history which both explain part of, not all, the features of the human thinking.Though the applications of these descriptions helped the AI researchers to step forward to the essence of human thinking, the gap between the two totally different thinking styles still provokes vigorous discussions.We believe that the real human brain uses images as representation of experience and knowledge from the outer world to generate connection and overlap these two thinking styles.The images mentioned here are generalized, including not only the low level information directly apperceived by the sensing apparatus of human body, but also high level information of experiences and knowledge by imitating and learning.Imitation is the way human brain mainly learns experience and knowledge from the outer environment, which played an extraordinary role in helping human brain reach present intelligence through the millions of years of evolution.By imitating human imaginal thinking, a novel AI frame is founded trying to solve some complicated engineering problems, which is possible to take both advantages of human intelligence and machine calculation capability.Brooks' achievements in action-based AI theory also show indirect evidence of some basic ideas of human imaginal thinking, which is different in approach but equally satisfactory in result. www.intechopen.comAdvances in Knowledge Representation 78 Just as the above mentioned, an effective AI frame has been constructed to solve some complicated engineering problems.Actually, when facing difficult engineering problems, lots of bio-inspired approaches, such as naturalistic biological synthesis approach and evolution inspired methodology have been tried and exhibited great advantage over traditional logical mathematic algorithms in improving system adaptability and robustness in uncertain or unpredictable situation.Take pipe-routing system for example, pipe-routing system design like aero-engine, not only a typical NP-hard problem in limited 3D space, must also extraordinarily depend on human experience.So as for pipe-routing, experienced human brain is often capable of providing more reasonable solutions within acceptable time than computer.So in the rest of this chapter, we'll focus on our current research: pipe route design based on imaginal thinking.A complete methodology will be given, and how computer simulates this process is to be discussed, which is mainly about the optimal path for each pipe.Furthermore, human's imaginal thinking is simulated with procedures of knowledge representation, pattern recognition, and logical deduction.The pipe assembly planning algorithm by imitating human imaginal thinking is then obtained, which effectively solved the problem of conceiving the shortest pipe route in 3D space with obstacles and constraints.Finally, the proposed pipe routing by imitating imaginal thinking is applied in an aero-engine pipe system design problem to testify the effectiveness and efficiency of the algorithm.The main idea of this chapter is by intercrossing investigations of the up-to-date research accomplishments in biology, psychology, artificial intelligence and robotics, trying to present the truth of human thinking so as to understand the fundamental processing style of human brain and neural network and explain the problems which has been confusing the artificial intelligence research, such as what the human thinking is, how human thinks, how human learns and how knowledge is represented and stored.Our work may bring us closer to the real picture of human thinking then a novel design methodology of pipe-routing system integrating the human imaginal thinking and logic machine computation capability is presented.The holistic layout of pipes is represented as images of feasible workspace, which reflect human experience and knowledge; the optimal path for each pipe is quickly decided by applying the translational configuration space obstacle and the improved visibility graph imitating human pipe-routing behavior.The simulation demonstrated the effectiveness and high efficiency of our pipe-routing design method.