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» AI planning: solutions for real world problems
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CHI
2010
ACM
13 years 7 months ago
How routine learners can support family coordination
Researchers have detailed the importance of routines in how people live and work, while also cautioning system designers about the importance of people's idiosyncratic behavi...
Scott Davidoff, John Zimmerman, Anind K. Dey
GECCO
2004
Springer
100views Optimization» more  GECCO 2004»
14 years 1 months ago
Transfer of Neuroevolved Controllers in Unstable Domains
In recent years, the evolution of artificial neural networks or neuroevolution has brought promising results in solving difficult reinforcement learning problems. But, like standa...
Faustino J. Gomez, Risto Miikkulainen
CEC
2009
IEEE
14 years 2 months ago
A clustering particle swarm optimizer for dynamic optimization
Abstract—In the real world, many applications are nonstationary optimization problems. This requires that optimization algorithms need to not only find the global optimal soluti...
Changhe Li, Shengxiang Yang
CORR
2011
Springer
160views Education» more  CORR 2011»
13 years 2 months ago
When is social computation better than the sum of its parts?
good solutions to complex problems. In many examples, individuals trying to solve superior global solution. This suggests that there may be general principles of information aggre...
Vadas Gintautas, Aric A. Hagberg, Luís M. A...
PPDP
2010
Springer
13 years 6 months ago
A declarative approach to robust weighted Max-SAT
The presence of uncertainty in the real world makes robustness to be a desired property of solutions to constraint satisfaction problems. Roughly speaking, a solution is robust if...
Miquel Bofill, Dídac Busquets, Mateu Villar...