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» An Integrated Instance-Based Learning Algorithm
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AAAI
2010
13 years 8 months ago
Integrating Sample-Based Planning and Model-Based Reinforcement Learning
Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...
Thomas J. Walsh, Sergiu Goschin, Michael L. Littma...
CORR
2004
Springer
140views Education» more  CORR 2004»
13 years 7 months ago
Integrating Defeasible Argumentation and Machine Learning Techniques
The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML app...
Sergio Alejandro Gómez, Carlos Iván ...
ATAL
2009
Springer
14 years 1 months ago
Integrating organizational control into multi-agent learning
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
KCAP
2011
ACM
12 years 10 months ago
Integrating knowledge capture and supervised learning through a human-computer interface
Some supervised-learning algorithms can make effective use of domain knowledge in addition to the input-output pairs commonly used in machine learning. However, formulating this a...
Trevor Walker, Gautam Kunapuli, Noah Larsen, David...
FLAIRS
1998
13 years 8 months ago
Interactively Training Pixel Classifiers
Manual generation of training examples for supervised learning is an expensive process. One way to reduce this cost is to produce training instances that are highly informative. T...
Justus H. Piater, Edward M. Riseman, Paul E. Utgof...