992 resultados para MX (Weapons system)
Resumo:
Systems of learning automata have been studied by various researchers to evolve useful strategies for decision making under uncertainity. Considered in this paper are a class of hierarchical systems of learning automata where the system gets responses from its environment at each level of the hierarchy. A classification of such sequential learning tasks based on the complexity of the learning problem is presented. It is shown that none of the existing algorithms can perform in the most general type of hierarchical problem. An algorithm for learning the globally optimal path in this general setting is presented, and its convergence is established. This algorithm needs information transfer from the lower levels to the higher levels. Using the methodology of estimator algorithms, this model can be generalized to accommodate other kinds of hierarchical learning tasks.
Resumo:
Mixtures of single odours were used to explore the receptor response profile across individual antennae of Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae). Seven odours were tested including floral and green-leaf volatiles: phenyl acetaldehyde, benzaldehyde, b-caryophyllene, limonene, a-pinene, 1-hexanol, 3Z-hexenyl acetate. Electroantennograms of responses to paired mixtures of odours showed that there was considerable variation in receptor tuning across the receptor field between individuals. Data from some moth antennae showed no additivity, which indicated a restricted receptor profile. Results from other moth antennae to the same odour mixtures showed a range of partial additivity. This indicated that a wider array of receptor types was present in these moths, with a greater percentage of the receptors tuned exclusively to each odour. Peripheral receptor fields show variation in the spectrum of response within a population (of moths) when exposed to high doses of plant volatiles. This may be related to recorded variation in host choice within moth populations as reported by other authors.