Learning to improve constraint-based scheduling
References (43)
Towards a general theory of action and time
Artif. Intell.
(1984)Constraint propagation with interval labels
Artif. Intell.
(1987)- et al.
Increasing tree efficiency for constraint satisfaction problems
Artif. Intell.
(1980) Consistency in networks of relations
Artif. Intell.
(1977)- et al.
Comparing stochastic planning to the acquisition of increasingly permissive plans for complex, uncertain domains
- et al.
Bottleneck identification using process chronologies
Knowledge-based scheduling and resource allocation in the CAMPS architecture
Concept learning using explanation based generalization as an abstraction mechanism
Finding new rules for incomplete theories
- et al.
Explanation-based generalization: an alternative view
Mach. Learn.
(1986)
Learning search control for a constraint-based scheduling system
Why Prodigy/EBL works
A study of explanation-based methods for inductive learning
Mach. Learn.
(1989)
A sufficient condition for backtrack-free search
J. ACM
(1982)
A hybrid approach to guaranteed effective control strategies
CHEF: a model of case-based planning
EMPRESS: expert mission planning and re-planning scheduling system
Decision-theoretic control of artificial intelligence scheduling systems
Combining empirical and analytical learning with version spaces
A heuristic approach to the discovery of macro-operators
Mach. Learn.
(1989)
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1997, Artificial IntelligenceCABINS: a framework of knowledge acquisition and iterative revision for schedule improvement and reactive repair
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1995, Artificial Intelligence in EngineeringCapturing scheduling knowledge from repair experiences
1994, International Journal of Human - Computer Studies
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