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» Learning behavior styles with inverse reinforcement learning
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COGSR
2011
71views more  COGSR 2011»
13 years 2 months ago
Psychological models of human and optimal performance in bandit problems
In bandit problems, a decision-maker must choose between a set of alternatives, each of which has a fixed but unknown rate of reward, to maximize their total number of rewards ov...
Michael D. Lee, Shunan Zhang, Miles Munro, Mark St...
GECCO
2008
Springer
138views Optimization» more  GECCO 2008»
13 years 8 months ago
Modular neuroevolution for multilegged locomotion
Legged robots are useful in tasks such as search and rescue because they can effectively navigate on rugged terrain. However, it is difficult to design controllers for them that ...
Vinod K. Valsalam, Risto Miikkulainen
ATAL
2011
Springer
12 years 7 months ago
Using iterated reasoning to predict opponent strategies
The field of multiagent decision making is extending its tools from classical game theory by embracing reinforcement learning, statistical analysis, and opponent modeling. For ex...
Michael Wunder, Michael Kaisers, John Robert Yaros...
ALT
1998
Springer
13 years 11 months ago
Synthesizing Learners Tolerating Computable Noisy Data
An index for an r.e. class of languages (by definition) generates a sequence of grammars defining the class. An index for an indexed family of recursive languages (by definition) ...
John Case, Sanjay Jain
ATAL
2009
Springer
14 years 1 months ago
Comparing trust mechanisms for monitoring aggregator nodes in sensor networks
Sensor nodes are often used to collect data from locations inaccessible or hazardous for humans. As they are not under normal supervision, these nodes are particularly susceptible...
Oly Mistry, Anil Gürsel, Sandip Sen