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AIPS
2006
15 years 4 months ago
Combining Stochastic Task Models with Reinforcement Learning for Dynamic Scheduling
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Malcolm J. A. Strens
EMNLP
2010
15 years 1 months ago
Domain Adaptation of Rule-Based Annotators for Named-Entity Recognition Tasks
Named-entity recognition (NER) is an important task required in a wide variety of applications. While rule-based systems are appealing due to their well-known "explainability...
Laura Chiticariu, Rajasekar Krishnamurthy, Yunyao ...
ICML
1996
IEEE
16 years 4 months ago
Representing and Learning Quality-Improving Search Control Knowledge
Generating good, production-quality plans is an essential element in transforming planners from research tools into real-world applications, but one that has been frequently overl...
M. Alicia Pérez
120
Voted
GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
15 years 4 months ago
Supply chain management sales using XCSR
The Trading Agent Competition in its category Supply Chain Management (TAC SCM) is an international forum where teams construct agents that control a computer assembly company in ...
María A. Franco, Ivette C. Martínez,...
AIPS
1998
15 years 4 months ago
Planning, Execution and Learning in a Robotic Agent
This paper presents the complete integrated planning, executing and learning robotic agent Rogue. We describe Rogue's task planner that interleaves high-level task planning w...
Karen Zita Haigh, Manuela M. Veloso