G. Santharam

Learn More
This paper discusses memory neuron networks as models for identification and adaptive control of nonlinear dynamical systems. These are a class of recurrent networks obtained by adding trainable temporal elements to feedforward networks that makes the output history-sensitive. By virtue of this capability, these networks can identify dynamical systems(More)
In this paper we consider the problem of reinforcement learning in a dynamically changing environment. In this context, we study the problem of adaptive control of finite-state Markov chains with a finite number of controls. The transition and payoff structures are unknown. The objective is to find an optimal policy which maximizes the expected total(More)
Imidacloprid 70 WS and imidacloprid 200 SL were evaluated for their efficacy against termites in sugarcane as sett dip and spray over setts in furrows in two field experiments. Sett dip of imidacloprid 70 WS at 0.1 and 0.15 per cent and spray over setts of imidacloprid 200 SL at 250 and 375 ml/ha-1 resulted in increased germination of setts. These(More)
  • 1