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» AI planning: solutions for real world problems
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GECCO
2000
Springer
138views Optimization» more  GECCO 2000»
13 years 11 months ago
Domain Knowledge and Representation in Genetic Algorithms for Real World Scheduling Problems
This paper discusses the issues that arise in the design and implementation of an industrialstrength evolutionary-based system for the optimization of the monthly work schedules f...
Ioannis T. Christou, Armand Zakarian
TBILLC
2005
Springer
14 years 29 days ago
Real World Multi-agent Systems: Information Sharing, Coordination and Planning
Abstract. Applying multi-agent systems in real world scenarios requires several essential research questions to be answered. Agents have to perceive their environment in order to t...
Frans C. A. Groen, Matthijs T. J. Spaan, Jelle R. ...
ECML
2005
Springer
14 years 1 months ago
Machine Learning of Plan Robustness Knowledge About Instances
Abstract. Classical planning domain representations assume all the objects from one type are exactly the same. But when solving problems in the real world systems, the execution of...
Sergio Jiménez, Fernando Fernández, ...
IEAAIE
2009
Springer
14 years 2 months ago
RFID Technology and AI Techniques for People Location, Orientation and Guiding
One of the main problems that we have to face when visiting public or official buildings (i.e hospitals or public administrations) is the lack of information and signs that can gui...
M. D. R-Moreno, Bonifacio Castaño, Melquiad...
ICTAI
2005
IEEE
14 years 1 months ago
Planning with POMDPs Using a Compact, Logic-Based Representation
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
Chenggang Wang, James G. Schmolze