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GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 10 months ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone
GECCO
2008
Springer
161views Optimization» more  GECCO 2008»
15 years 7 months ago
An evolutionary design technique for collective communications on optimal diameter-degree networks
Scheduling collective communications (CC) in networks based on optimal graphs and digraphs has been done with the use of the evolutionary techniques. Inter-node communication patt...
Jirí Jaros, Vaclav Dvorak
GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
16 years 17 days ago
Reducing the number of transistors in digital circuits using gate-level evolutionary design
This paper shows that the evolutionary design of digital circuits which is conducted at the gate level is able to produce human-competitive circuits at the transistor level. In ad...
Zbysek Gajda, Lukás Sekanina
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
16 years 17 days ago
SDR: a better trigger for adaptive variance scaling in normal EDAs
Recently, advances have been made in continuous, normal– distribution–based Estimation–of–Distribution Algorithms (EDAs) by scaling the variance up from the maximum–like...
Peter A. N. Bosman, Jörn Grahl, Franz Rothlau...
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
15 years 10 months ago
Towards estimating nadir objective vector using evolutionary approaches
Nadir point plays an important role in multi-objective optimization because of its importance in estimating the range of objective values corresponding to desired Pareto-optimal s...
Kalyanmoy Deb, Shamik Chaudhuri, Kaisa Miettinen