-
4
-
-
0001410750
-
A new factor in evolution
-
Baldwin, J. M. 1896. A new factor in evolution. The American Naturalist 30:441-451.
-
(1896)
The American Naturalist
, vol.30
, pp. 441-451
-
-
Baldwin, J.M.1
-
5
-
-
0032208335
-
Elevator group control using multiple reinforcement learning agents
-
Crites, R. H., and Barto, A. G. 1998. Elevator group control using multiple reinforcement learning agents. Machine Learning 33(2-3):235-262.
-
(1998)
Machine Learning
, vol.33
, Issue.2-3
, pp. 235-262
-
-
Crites, R.H.1
Barto, A.G.2
-
7
-
-
0000211184
-
How learning can guide evolution
-
Hinton, G.E., and Nowlan, S. J. 1987. How learning can guide evolution. Complex Systems 1:495-502.
-
(1987)
Complex Systems
, vol.1
, pp. 495-502
-
-
Hinton, G.E.1
Nowlan, S.J.2
-
8
-
-
0037253062
-
The vision of autonomie computing
-
Kephart, J. O., and Chess, D. M. 2003. The vision of autonomie computing. Computer 36(1):41-50.
-
(2003)
Computer
, vol.36
, Issue.1
, pp. 41-50
-
-
Kephart, J.O.1
Chess, D.M.2
-
11
-
-
0000123778
-
Self-improving reactive agents based on reinforcement learning, planning, and teaching
-
Lin, L.-J. 1992. Self-improving reactive agents based on reinforcement learning, planning, and teaching. Machine Learning 8(3-4):293-321.
-
(1992)
Machine Learning
, vol.8
, Issue.3-4
, pp. 293-321
-
-
Lin, L.-J.1
-
12
-
-
0027684215
-
Prioritized sweeping: Reinforcement learning with less data and less time
-
Moore, A. W., and Atkeson, C. G. 1993. Prioritized sweeping: Reinforcement learning with less data and less time. Machine Learning 13(1):103-130.
-
(1993)
Machine Learning
, vol.13
, Issue.1
, pp. 103-130
-
-
Moore, A.W.1
Atkeson, C.G.2
-
13
-
-
33646398129
-
Neural fitted Q iteration - First experiences with a data efficient neural reinforcement learning method
-
Reidmiller, M. 2005. Neural fitted Q iteration - first experiences with a data efficient neural reinforcement learning method. In Proceedings of the Sixteenth European Conference on Machine Learning, 317-328.
-
(2005)
Proceedings of the Sixteenth European Conference on Machine Learning
, pp. 317-328
-
-
Reidmiller, M.1
-
15
-
-
0036594106
-
Evolving neural networks through augmenting topologies
-
Stanley, K. O., and Miikkulainen, R. 2002. Evolving neural networks through augmenting topologies. Evolutionary Computation 10(2):99-127.
-
(2002)
Evolutionary Computation
, vol.10
, Issue.2
, pp. 99-127
-
-
Stanley, K.O.1
Miikkulainen, R.2
-
17
-
-
84898939480
-
Policy gradient methods for reinforcement learning with function approximation
-
Sutton, R.; McAllester, D.; Singh, S.; and Mansour, Y. 2000. Policy gradient methods for reinforcement learning with function approximation. In Advances in Neural Information Processing Systems, 1057-1063.
-
(2000)
Advances in Neural Information Processing Systems
, pp. 1057-1063
-
-
Sutton, R.1
McAllester, D.2
Singh, S.3
Mansour, Y.4
-
18
-
-
0000985504
-
TD-Gammon, a self-teaching backgammon program, achieves master-level play
-
Tesauro, G. 1994. TD-Gammon, a self-teaching backgammon program, achieves master-level play. Neural Computation 6(2):215-219.
-
(1994)
Neural Computation
, vol.6
, Issue.2
, pp. 215-219
-
-
Tesauro, G.1
-
19
-
-
4544366889
-
Utility functions in autonomie systems
-
Walsh, W. E.; Tesauro, G.; Kephart, J. O.; and Das, R. 2004. Utility functions in autonomie systems. In Proceedings of the International Conference on Autonomic Computing, 70-77.
-
(2004)
Proceedings of the International Conference on Autonomic Computing
, pp. 70-77
-
-
Walsh, W.E.1
Tesauro, G.2
Kephart, J.O.3
Das, R.4
-
21
-
-
33646714634
-
Evolutionary function approximation for reinforcement learning
-
To appear
-
Whiteson, S., and Stone, P. 2006. Evolutionary function approximation for reinforcement learning. Journal of Machine Learning Research. To appear.
-
(2006)
Journal of Machine Learning Research
-
-
Whiteson, S.1
Stone, P.2
-
22
-
-
0033362601
-
Evolving artificial neural networks
-
Yao, X. 1999. Evolving artificial neural networks. Proceedings of the IEEE 87(9):1423-1447.
-
(1999)
Proceedings of the IEEE
, vol.87
, Issue.9
, pp. 1423-1447
-
-
Yao, X.1
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