Machine Learning
Using collective intelligence to route Internet traffic
Proceedings of the 1998 conference on Advances in neural information processing systems II
Learning instance-independent value functions to enhance local search
Proceedings of the 1998 conference on Advances in neural information processing systems II
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Neuro-Dynamic Programming
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
A Note on the Universal Approximation Capability of Support Vector Machines
Neural Processing Letters
A Necessary Condition of Convergence for Reinforcement Learning with Function Approximation
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Value Function Based Production Scheduling
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning as Applied to Stochastic Optimization for Standard Cell Placement
ICCD '98 Proceedings of the International Conference on Computer Design
Multi-Machine Scheduling - A Multi-Agent Learning Approach
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Learning evaluation functions for global optimization
Learning evaluation functions for global optimization
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
A reinforcement learning approach to job-shop scheduling
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Ant colony optimization for resource-constrained project scheduling
IEEE Transactions on Evolutionary Computation
Using granular computing model to induce scheduling knowledge in dynamic manufacturing environments
International Journal of Computer Integrated Manufacturing
Adaptive sampling based large-scale stochastic resource control
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Adaptive stochastic resource control: a machine learning approach
Journal of Artificial Intelligence Research
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The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources' availabilities in real life production processes and subsumes open-shop, job-shop, and flow-shop scheduling as special cases. We present here an application of machine learning to adapt simple greedy strategies for the RCPSP. Iterative repair steps are applied to an initial schedule which neglects resource constraints. The rout-algorithm of reinforcement learning is used to learn an appropriate value function which guides the search. We propose three different ways to define the value function and we use the support vector machine (SVM) for its approximation. The specific properties of the SVM allow to reduce the size of the training set and SVM shows very good generalization behavior also after short training. We compare the learned strategies to the initial greedy strategy for different benchmark instances of the RCPSP.