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Preface to special issue on planning and scheduling

Published online by Cambridge University Press:  01 September 2010

Roman Barták ,
Amedeo Cesta ,
Lee McCluskey  and
Miguel A. Salido
Roman Barták*
Affiliation:
Faculty of Mathematics and Physics, Charles University in Prague, Malostranské nám. 2/25, 118 00 Praha 1, Czech Republic; e-mail: [email protected]
Amedeo Cesta*
Affiliation:
Consiglio Nazionale delle Ricerche, Instituto di Scienze e Tecnologie della Cognizione, Via S. Martino della Battaglia 44, I-00185 Rome, Italy; e-mail: [email protected]
Lee McCluskey*
Affiliation:
School of Computing and Engineering, University of Huddersfield, Queensgate, Huddersfield, West Yorkshire, HD1 3DH, UK; e-mail: [email protected]
Miguel A. Salido*
Affiliation:
Instituto de Automática e Informática Industrial, Universidad Politécnica de Valencia, Camino de vera s/n 46020, Valencia, Spain; e-mail: [email protected]
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Abstract

Planning, scheduling and constraint satisfaction are important areas in artificial intelligence (AI) with broad practical applicability. Many real-world problems can be formulated as AI planning and scheduling (P&S) problems, where resources must be allocated to optimize overall performance objectives. Frequently, solving these problems requires an adequate mixture of planning, scheduling and resource allocation to competing goal activities over time in the presence of complex state-dependent constraints. Constraint satisfaction plays an important role in solving such real-life problems, and integrated techniques that manage P&S with constraint satisfaction are particularly useful. Knowledge engineering supports the solution of such problems by providing adequate modelling techniques and knowledge extraction techniques for improving the performance of planners and schedulers. Briefly speaking, knowledge engineering tools serve as a bridge between the real world and P&S systems.

Type
Other
Information
The Knowledge Engineering Review , Volume 25 , Special Issue 3: Planning and scheduling , September 2010 , pp. 247 - 248
Copyright
Copyright © Cambridge University Press 2010

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