Fetching the paper…
Reading the bibliography…
Despite recent progress in robot learning, it still remains a challenge to program a robot to deal with open-ended object manipulation tasks.
S. Thrun and T. M. Mitchell, “Lifelong robot learning,” Robotics and autonomous systems , 1995
1995
Earlier work this paper cites.
P. Larrañaga and J. A. Lozano, Estimation of distribution algorithms: A new tool for evolutionary computation . Springer Science & Business Media, 2001
2001
Earlier work this paper cites.
B. Wilson, D. Cappelleri, T. Simpson, and M. Frecker, “Efficient pareto frontier exploration using surrogate approximations,” Optimization and Engineering , 2001
2001
Earlier work this paper cites.
Y. Jin, “A comprehensive survey of fitness approximation in evolutionary computation,” Soft Computing , 2005
2005
Earlier work this paper cites.
M. Asada, K. Hosoda, Y. Kuniyoshi, H. Ishiguro, T. Inui, Y. Yoshikawa, M. Ogino, and C. Yoshida, “Cognitive developmental robotics: A survey,” IEEE transactions on autonomous mental development , 2009
2009
Earlier work this paper cites.
J. Lehman and K. Stanley, “Abandoning objectives: Evolution through the search for novelty alone,” Evolutionary computation , 2011
2011
Earlier work this paper cites.
J. Lehman and K. O. Stanley, “Evolving a diversity of virtual creatures through novelty search and local competition,” in Proceedings of the 13th annual conference on Genetic and evolutionary computation , 2011
2011
Earlier work this paper cites.
——, “Surrogate-assisted evolutionary computation: Recent advances and future challenges,” Swarm and Evolutionary Computation , 2011
2011
Earlier work this paper cites.
A. Cully and J.-B. Mouret, “Behavioral repertoire learning in robotics,” in Proceedings of the 15th annual conference on Genetic and evolutionary computation , 2013
2013
Cited alongside, same era.
2014
Cited alongside, same era.
I. Giagkiozis and P. Fleming, “Pareto front estimation for decision making,” Evolutionary computation , 2014
2014
Cited alongside, same era.
2015
Cited alongside, same era.
R. Cheng, Y. Jin, K. Narukawa, and B. Sendhoff, “A multiobjective evolutionary algorithm using gaussian process-based inverse modeling,” IEEE Transactions on Evolutionary Computation , 2015
G. Corriveau, R. Guilbault, A. Tahan, and R. Sabourin, “Bayesian network as an adaptive parameter setting approach for genetic algorithms,” Complex & Intelligent Systems , 2016
2016
Later among the works it cites.
A. Cully and Y. Demiris, “Quality and diversity optimization: A unifying modular framework,” IEEE Transactions on Evolutionary Computation , 2017
2017
Later among the works it cites.
T. Chugh, K. Sindhya, J. Hakanen, and K. Miettinen, “A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms,” Soft Computing , 2017
2017
Later among the works it cites.
2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2015
Cited alongside, same era.
M. Tabatabaei, J. Hakanen, M. Hartikainen, K. Miettinen, and K. Sindhya, “A survey on handling computationally expensive multiobjective optimization problems using surrogates: non-nature inspired methods,” Structural and Multidisciplinary Optimization , 2015
2015
Cited alongside, same era.
D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” International Conference for Learning Representations , 2015
2015
Cited alongside, same era.
2016
Cited alongside, same era.
2018
Later among the works it cites.
A. Gaier, A. Asteroth, and J.-B. Mouret, “Data-efficient design exploration through surrogate-assisted illumination,” Evol. Comput. , 2018
2018
Later among the works it cites.
2019
Later among the works it cites.
2019
Later among the works it cites.