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The mountain car problem appeared first in Andrew Moore's PhD thesis (1990). [1] It was later more strictly defined in Singh and Sutton's reinforcement learning paper with eligibility traces. [2] The problem became more widely studied when Sutton and Barto added it to their book Reinforcement Learning: An Introduction (1998). [3]
Pell's equation for n = 2 and six of its integer solutions. Pell's equation, also called the Pell–Fermat equation, is any Diophantine equation of the form =, where n is a given positive nonsquare integer, and integer solutions are sought for x and y.
The method is an extension of the Newmark's direct integration method originally proposed by Nathan M. Newmark in 1943. It was applied to the sliding block problem in a lecture delivered by him in 1965 in the British Geotechnical Association's 5th Rankine Lecture in London and published later in the Association's scientific journal Geotechnique. [1]
To use a finite difference method to approximate the solution to a problem, one must first discretize the problem's domain. This is usually done by dividing the domain into a uniform grid (see image). This means that finite-difference methods produce sets of discrete numerical approximations to the derivative, often in a "time-stepping" manner.
the slope field is an array of slope marks in the phase space (in any number of dimensions depending on the number of relevant variables; for example, two in the case of a first-order linear ODE, as seen to the right). Each slope mark is centered at a point (,,, …,) and is parallel to the vector
General solutions are a class of solutions within descriptive geometry that contain all possible solutions to a problem. The general solution is represented by a single, three-dimensional object, usually a cone, the directions of the elements of which are the desired direction of viewing (projection) for any of an infinite number of solution views.
When integrating a differential equation numerically, one would expect the requisite step size to be relatively small in a region where the solution curve displays much variation and to be relatively large where the solution curve straightens out to approach a line with slope nearly zero. For some problems this is not the case.
(0) real beam, (1) shear and moment, (2) conjugate beam, (3) slope and displacement The conjugate-beam methods is an engineering method to derive the slope and displacement of a beam. A conjugate beam is defined as an imaginary beam with the same dimensions (length) as that of the original beam but load at any point on the conjugate beam is ...