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» Policy Learning for Motor Skills
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AIIDE
2008
13 years 7 months ago
Intelligent Trading Agents for Massively Multi-player Game Economies
As massively multi-player gaming environments become more detailed, developing agents to populate these virtual worlds as capable non-player characters poses an increasingly compl...
John Reeder, Gita Sukthankar, Michael Georgiopoulo...
AGENTS
2001
Springer
13 years 9 months ago
Hierarchical multi-agent reinforcement learning
In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamz...
ATAL
2010
Springer
13 years 6 months ago
Linear options
Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
Jonathan Sorg, Satinder P. Singh
DSRT
2006
IEEE
13 years 11 months ago
Grid-enabling FIRST: Speeding Up Simulation Applications Using WinGrid
The vision of grid computing is to make computational power, storage capacity, data and applications available to users as readily as electricity and other utilities. Grid infrast...
Navonil Mustafee, Anders Alstad, Bjorn Larsen, Sim...