Reinforcement learning with hierarchies of machines
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Between MDPs and semi-MDPs: a framework for temporal abstraction in reinforcement learning
Artificial Intelligence
Discovering Hierarchy in Reinforcement Learning with HEXQ
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
An Overview of MAXQ Hierarchical Reinforcement Learning
SARA '02 Proceedings of the 4th International Symposium on Abstraction, Reformulation, and Approximation
State abstraction for programmable reinforcement learning agents
Eighteenth national conference on Artificial intelligence
Recent Advances in Hierarchical Reinforcement Learning
Discrete Event Dynamic Systems
Discovery of climate indices using clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
SimEd: Simulating Education as a Multi Agent System
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Cluster Analysis for Gene Expression Data: A Survey
IEEE Transactions on Knowledge and Data Engineering
Finding community structure in mega-scale social networks: [extended abstract]
Proceedings of the 16th international conference on World Wide Web
Segmentation and Automated Social Hierarchy Detection through Email Network Analysis
Advances in Web Mining and Web Usage Analysis
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Concurrent hierarchical reinforcement learning
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
Colony Evolution in Social Networks Based on Multi-agent System
ICNC '09 Proceedings of the 2009 Fifth International Conference on Natural Computation - Volume 04
Data clustering: 50 years beyond K-means
Pattern Recognition Letters
Dynamic and adaptive replication for large-scale reliable multi-agent systems
Software engineering for large-scale multi-agent systems
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
Computer Science Review
Survey of clustering algorithms
IEEE Transactions on Neural Networks
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The quality of K-12 education has been a major concern in the nation for years. School systems, just like many other social networks, appear to have a hierarchical structure. Understanding this structure could be the key to better evaluating student performance and improving school quality. Many studies have been focusing on detecting hierarchical structure by using hierarchical clustering algorithms. The authors design an interaction-based similarity measure to accomplish hierarchical clustering in order to detect hierarchical structures in social networks e.g. school district networks. This method uses a multi-agent system, for it is based on agent interactions. With the network structure detected, they also built a model, which is based on the MAXQ algorithm, to decompose the funding policy task into subtasks and then evaluate these subtasks by using funding distribution policies from past years and looking for possible relationships between student performances and funding policies. For the experiment, the authors used real school data from Bexar county's 15 school districts in Texas. The first result shows that their interaction-based method is able to generate meaningful clustering and dendrograms for social networks. Additionally the authors' policy evaluation model is able to evaluate funding policies from the past three years in Bexar County and conclude that increasing funding does not necessarily have a positive impact on student performance and it is generally not the case that the more is spent, the better.