LEADER 00000cam  2200625Ia 4500 
001    261134771 
003    OCoLC 
005    20210108112145.4 
006    m     o  d         
007    cr cnu---unuuu 
008    081007s2001    si a    ob    001 0 eng d 
010    |z2001275891 
020    9789812811844 
020    9812811842 
020    1281960748 
020    9781281960740 
035    (OCoLC)261134771|z(OCoLC)505150585|z(OCoLC)646768587
035    Ebook Central Science & Technology Ebook Subscription 
035    skip4alma 
040    N$T|beng|epn|cN$T|dOCLCQ|dUBY|dIDEBK|dE7B|dOCLCQ|dOCLCF
049    txum 
050  4 QA76.76.I58|bL58 2001eb 
072  7 COM|x005030|2bisacsh 
072  7 COM|x004000|2bisacsh 
072  7 UYQM|2bicssc 
082 04 006.3|222eb 
100 1  Liu, Jiming,|d1962- 
245 10 Autonomous agents and multi-agent systems :|bexplorations 
       in learning, self-organization, and adaptive computation /
       |cJiming Liu. 
260    Singapore ;|aRiver Edge, N.J. :|bWorld Scientific,|c2001. 
300    1 online resource (xx, 280 pages) :|billustrations 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    data file|2rda 
500    "By request of the author, the royalty for this book goes 
       to United Nations Children Fund (UNICEF) and a youth 
       public welfare fund." 
504    Includes bibliographical references (pages 257-276) and 
505 0  Ch. Introduction. 1.1. What is an agent? 1.2. Basic 
       questions and fundamental issues. 1.3. Learning. 1.4. 
       Neural agents. 1.5. Evolutionary agents. 1.6. Learning in 
       cooperative agents. 1.7. Computational architectures. 1.8.
       Agent behavioral learning -- ch. 2. Behavioral modeling, 
       planning, and learning. 2.1. Manipulation behaviors. 2.2. 
       Modeling and planning manipulation behaviors. 2.3. 
       Manipulation behavioral learning. 2.4. Summary. 2.5. Other
       modeling, planning, and learning methods. 2.6. 
       Bibliographical and historical remarks -- ch. 3. Synthetic
       autonomy. 3.1. Synthetic autonomy based on behavioral self
       -organization. 3.2. Behavioral self-organization. 3.3. 
       Summary. 3.4. Bibliographical and historical remarks -- 
       ch. 4. Dynamics of distributed computation. 4.1. 
       Definitions. 4.2. Overview of the approach. 4.3. Dynamics 
       of agent-based distributed search. 4.4. Remarks. 4.5. 
       Summary. 4.6. Bibliographical and historical remarks -- 
       ch. 5. Self-organized autonomy in multi-agent systems. 
       5.1. Collective vision and motion. 5.2. Self-organized 
       vision for image feature detection and tracking. 5.3. Self
       -organized motion in group robots. 5.4. Summary. 5.5. 
       Bibliographical and historical remarks -- ch. 6. Autonomy-
       oriented computation. 6.1. Terminology. 6.2. The adaptive 
       self-organizing behavior-based agents. 6.3. The general 
       characteristics of agents. 6.4. The adaptive reproduce-and
       -diffuse (aR-D) algorithm. 6.5. Examples. 6.6. 
       Computational costs. 6.7. Comparisons with conventional 
       segmentation approaches. 6.8. Effects of behavioral 
       characteristics on agent-based search. 6.9. Parameters 
       affecting agent computation. 6.10. Dynamics of autonomous 
       agents. 6.11. Balance between learning and evolution. 
       6.12. Summary. 6.13. Bibliographical and historical 
       remarks -- ch. 7. Dynamics and complexity of autonomy-
       oriented computation. 7.1. Decentralized agent behaviors. 
       7.2. Goal-attainability. 7.3. Population dynamics. 7.4. 
       Examples. 7.5. Complexity of autonomy-oriented 
       computation. 7.6. Summary. 7.7. Bibliographical and 
       historical remarks. 
506    Available only to authorized UTEP users. 
520    An autonomous agent is a computational system that 
       acquires sensory data from its environment and decides by 
       itself how to relate the external stimulus to its 
       behaviours in order to attain certain goals. Responding to
       different stimuli received from its task environment, the 
       agent may select and exhibit different behavioural 
       patterns. The behavioural patterns may be carefully 
       predefined or dynamically acquired by the agent based on 
       some learning and adaptation mechanism(s). In order to 
       achieve structural flexibility, reliability through 
       redundancy, adaptability, and reconfigurability in real-
       world tasks, some researchers have started to address the 
       issue of multiagent cooperation. Broadly speaking, the 
       power of autonomous agents lies in their ability to deal 
       with unpredictable, dynamically changing environments. 
       Agent-based systems are becoming one of the most important
       computer technologies, holding out many promises for 
       solving real-world problems. The aims of this book are to 
       provide a guided tour to the pioneering work and the major
       technical issues in agent research, and to give an in-
       depth discussion on the computational mechanisms for 
       behavioural engineering in autonomous agents. Through a 
       systematic examination, the book attempts to provide the 
       general design principles for building autonomous agents 
       and the analytical tools for modelling the emerged 
       behavioural properties of a multiagent system. 
588 0  Print version record. 
650  0 Intelligent agents (Computer software) 
650  0 Self-organizing systems. 
655  0 Electronic books. 
776 08 |iPrint version:|aLiu, Jiming, 1962-|tAutonomous agents 
       and multi-agent systems.|dSingapore ; River Edge, N.J. : 
       World Scientific, 2001|z9810242824|z9789810242824|w(DLC)  
856 40 |uhttp://0-ebookcentral.proquest.com.lib.utep.edu/lib/utep
       /detail.action?docID=1681286|zTo access this resource 
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