By N. R. Jennings, M. Wooldridge (auth.), Nicholas R. Jennings, Michael J. Wooldridge (eds.)
Agents signify a thrilling and promising new method of construction quite a lot of software program purposes. brokers are self sustaining problem-solving entities which are in a position to flexibly remedy difficulties in complicated, dynamic environments, with out receiving everlasting information from the user.
Agent know-how: Foundations, functions and Markets is the 1st publication to supply an integrative presentation of the problems, demanding situations and good fortune of designing, construction and utilizing agent purposes. The chapters awarded are written via the world over best gurus within the box. The e-book presents, for a basic viewers, a different evaluation on agent know-how purposes, starting from an creation to the technical foundations to studies on facing particular agent platforms in practice.
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Extra resources for Agent Technology: Foundations, Applications, and Markets
The debates as to which of them is 'better' are academic, sterile, and rather too premature to get into. Since each type has (or promises) its own strengths and deficiencies, the trick, as always, is to maximize the strengths and minimize the deficiencies of the most relevant technique for your particular purpose. Frequently, one way of doing this is to adopt a hybrid approach, like Maes (199Ib), which brought together some ofthe strengths ofboth the deliberative and reactive paradigms. In such a case the reactive component, which would take precedence over the deliberative one, brings about the following benefits: robustness, faster response times, and adaptability.
Brooks argues that this hypothesis obviates the need for symbolic representations or models because the world becomes its own best model. Furthermore, this model is always kept up-to-date since the system is connected to the world via sensors and/or actuators. Hence, the reactive agents hypothesis may be stated as folIows: intelligent agent systems can be developed from simple agents that do not have internal symbolic models, and whose 'intelligence' derives from the emergent behavior ofthe interactions ofthe various agents.
Weid, D. (1994) A softbot-based interface to the Internet. Communications the ACM, 37 (7),72-76. 01 Ferber, J. (1994) Simulating with reactive agents. In: E. Hillebrand, 1. ) Many Agent Simulation and Artificial Life, 8-28. lOS Press, Amsterdam. , Muller, 1. , Pischel, M. (1996) Unifying control in a layered agent architecture. Technical Report TM-94-05, German Research Center for AI - (DFKI GmbH). Genesereth, M. , Ketchpel, S. P. (1994) Software agents. Communications olthe ACM, 37(7), 48-53.
Agent Technology: Foundations, Applications, and Markets by N. R. Jennings, M. Wooldridge (auth.), Nicholas R. Jennings, Michael J. Wooldridge (eds.)