374 search results - page 25 / 75 » Multiagent Reinforcement Learning: Theoretical Framework and... |
ICRA
2003
IEEE
14 years 29 days ago
2003
IEEE
Existing task allocation algorithms generally do not consider the effects of task interaction, such as interference, but instead assume that tasks are independent. That assumptio...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
In the multi-view learning paradigm, the input variable is partitioned into two different views X1 and X2 and there is a target variable Y of interest. The underlying assumption i...
AIIDE
2009
13 years 8 months ago
2009
Dynamic scripting is a reinforcement learning algorithm designed specifically to learn appropriate tactics for an agent in a modern computer game, such as Neverwinter Nights. This...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Multiagent Inductive Learning is the problem that groups of agents face when they want to perform inductive learning, but the data of interest is distributed among them. This pape...
ATAL
2007
Springer
14 years 1 months ago
2007
Springer
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...