MIT Press.

de Finetti Bruno, (1992 [1931]), "On the Subjective Meaning of Probability," in Paola Monari & Daniela Cocchi (eds), Bruno de Finetti: Probabilità e induzione (Induction and Probability), Bologna, CLUEB, 298-329. Title Link: Maria Carla Galavotti. "Pragmatism and the Birth of Subjective Probability". European Journal of Pragmatism and American Philosophy [Online], XI-1 | 2019, Online since 19 July 2019, connection on 21 July 2019.

Chalasani et al. show that this problem is Korf (1985) presents a method for learning macrooperators in NP, but NPcompleteness is open. Tadepalli (1991a, and shows that the method is applicable 1991b) shows how macro tables are polynomially PAClearnable to serially decomposable problems.

Abstract Missing

The Hopfield network (Hopfield, 1982,1984) provides a simple model of an associative memory in a neuronal structure. This model, however, is based on highly artificial assumptions, especially the use of formal-two state neurons (Hopfield,1982) or graded-response neurons (Hopfield, 1984).

Box 808 (L-426), Livermore, Ca. 94550 A simple architecture and algorithm for analytically guaranteed associative memorystorage of analog patterns, continuous sequences, and chaotic attractors in the same network is described. A matrix inversion determines network weights, given prototype patterns to be stored.

The self-organization of recurrent feature-discovery networks is studied from the perspective of dynamical systems. Bifurcation theory reveals parameter regimesin which multiple equilibria or limit cycles coexist with the equilibrium at which the networks perform principal component analysis.

Coherent oscillatory activity in large networks of biological or artificial neuralunits may be a useful mechanism for coding information pertaining to a single perceptual object or for detailing regularities within a data set. We consider the dynamics of a large array of simple coupled oscillators under a variety of connection schemes. Of particular interest is the rapid and robust phase-locking that results from a "sparse" scheme where each oscillator is strongly coupled to a tiny, randomly selected, subset of its neighbors.

The main point of this paper is that stochastic neural networks have a mathematical structure that corresponds quite closely with that of quantum field theory. Neural network Liouvillians and Lagrangians can be derived, just as can spin Hamiltonians and Lagrangians in QFf. It remains to show the efficacy of such a description.

Combining neuropharmacological experiments with computational modeling, we have shown that cholinergic modulation may enhance associative memory function in piriform (olfactory) cortex. We have shown that the acetylcholine analogue carbachol selectively suppresses synaptic transmission between cells within piriform cortex, while leaving input connections unaffected. When tested in a computational model of piriform cortex, this selective suppression, applied during learning, enhances associative memory performance.