Zobrazeno 1 - 10
of 17
pro vyhledávání: '"V.V. Phansalkar"'
Autor:
V.V. Phansalkar, M.A.L. Thathachar
Publikováno v:
IEEE Transactions on Neural Networks. 6:398-406
A feedforward network composed of units of teams of parameterized learning automata is considered as a model of a reinforcement learning system. The internal state vector of each learning automaton is updated using an algorithm consisting of a gradie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5470d0427b2a75e28547041b89cb546a
https://doi.org/10.1109/72.363475
https://doi.org/10.1109/72.363475
Autor:
V.V. Phansalkar, M. A. L. Thathachar
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics. 25:1459-1469
Learning algorithms for feedforward connectionist systems in a reinforcement learning environment are developed and analyzed in this paper. The connectionist system is made of units of groups of learning automata. The learning algorithm used is the L
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::822aa8ea3c0e65830209475f2c6c2380
https://doi.org/10.1109/21.467711
https://doi.org/10.1109/21.467711
Publikováno v:
Proceedings Mathematical Sciences. 104:279-294
This paper considers a multi-person discrete game with random payoffs. The distribution of the random payoff is unknown to the players and further none of the players know the strategies or the actual moves of other players. A class of absolutely exp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97f365d81dbb8b1d2117b606f053030c
https://doi.org/10.1007/bf02830892
https://doi.org/10.1007/bf02830892
Autor:
V.V. Phansalkar, M.A.L. Thathachar
Publikováno v:
[Proceedings 1992] IJCNN International Joint Conference on Neural Networks.
A feedforward network composed of units of teams of parameterized learning automata is considered as a model of a reinforcement learning system. The parameters of each learning automaton are updated using an algorithm consisting of a gradient followi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0561ef5ecd936ebc017091f6df3ef36f
https://doi.org/10.1109/ijcnn.1992.227089
https://doi.org/10.1109/ijcnn.1992.227089
Autor:
V.V. Phansalkar, P. S. Sastry
Publikováno v:
IEEE transactions on neural networks. 5(3)
In this letter, the back-propagation algorithm with the momentum term is analyzed. It is shown that all local minima of the sum of least squares error are stable. Other equilibrium points are unstable. >
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::acf1e89e39ea5a081b0ed990c2c7d44c
https://pubmed.ncbi.nlm.nih.gov/18267819
https://pubmed.ncbi.nlm.nih.gov/18267819
Autor:
V.V. Phansalkar, M.A.L. Thathachar
Publikováno v:
[Proceedings] 1991 IEEE International Joint Conference on Neural Networks.
A model made of units of teams of learning automata is developed for the three layer pattern classifier. The algorithm is approximated by an ordinary differential equation (ODE), using weak convergence methods. The pattern recognition problem is pose
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f2e61a6de7cb6f228212bc74a59a712
https://doi.org/10.1109/ijcnn.1991.170725
https://doi.org/10.1109/ijcnn.1991.170725
Publikováno v:
IndraStra Global.
Weak convergence methods are used to analyse generalized learning automata algorithms. The REINFORCE algorithm has been analysed. It is shown by an example that this algorithm can exhibit unbounded behaviour. A modification based on constrained optim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::757ae34d61e9b97ff97fb17626c1fd1c
https://igi.indrastra.com/items/show/194615
https://igi.indrastra.com/items/show/194615
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