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» Modeling Complex Domains of Actions and Change
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ICML
2001
IEEE
16 years 17 days ago
Continuous-Time Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Mohammad Ghavamzadeh, Sridhar Mahadevan
HCI
2009
14 years 9 months ago
Rapid Development of Scoped User Interfaces
As the demand for domain- and formalism-specific visual modelling environments grows, the need to rapidly construct complex User Interfaces (UIs) increases. In this paper, we propo...
Denis Dubé, Jacob Beard, Hans Vangheluwe
AAAI
2008
15 years 2 months ago
Adaptive Management of Air Traffic Flow: A Multiagent Coordination Approach
This paper summarizes recent advances in the application of multiagent coordination algorithms to air traffic flow management. Indeed, air traffic flow management is one of the fu...
Kagan Tumer, Adrian K. Agogino
ICML
2004
IEEE
16 years 17 days ago
Learning and discovery of predictive state representations in dynamical systems with reset
Predictive state representations (PSRs) are a recently proposed way of modeling controlled dynamical systems. PSR-based models use predictions of observable outcomes of tests that...
Michael R. James, Satinder P. Singh
IRI
2009
IEEE
15 years 6 months ago
Ontology-based Information Model Development for Science Information Reuse and Integration
Scientific digital libraries serve complex and evolving research communities. Justifications for the development of scientific digital libraries include the desire to preserve sci...
J. Steven Hughes, Daniel J. Crichton, Chris Mattma...