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» Validation Method for Intelligent Systems
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ATAL
2007
Springer
16 years 16 days ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
ATAL
2003
Springer
15 years 11 months ago
Coalition formation with uncertain heterogeneous information
Coalition formation methods allow agents to join together and are thus necessary in cases where tasks can only be performed cooperatively by groups. This is the case in the Reques...
Sarit Kraus, Onn Shehory, Gilad Taase
ATAL
2010
Springer
15 years 7 months ago
Deception in networks of mobile sensing agents
Recent studies have investigated how a team of mobile sensors can cope with real world constraints, such as uncertainty in the reward functions, dynamically appearing and disappea...
Viliam Lisý, Roie Zivan, Katia P. Sycara, M...
ATAL
2010
Springer
15 years 7 months ago
Combining manual feedback with subsequent MDP reward signals for reinforcement learning
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...
W. Bradley Knox, Peter Stone
ATAL
2010
Springer
15 years 7 months ago
Enumeration and exact design of weighted voting games
In many multiagent settings, situations arise in which agents must collectively make decisions while not every agent is supposed to have an equal amount of influence in the outcom...
Bart de Keijzer, Tomas Klos, Yingqian Zhang