Excerpt from Physical Idealization as Plausible Inference, Vol. 4
Let us make the simplifying assumption, for the moment, that the appropriate fix, here is to associate a small resistance with the wire. Thus, in most cases, we wish to approximate a wire as a short circuit; here, we wish to approximate it as a resistor of very low resistance. One way to accomplish this would be to change the basic model of a wire to be a small resistor; to apply this uniformly to all circuits; and then to use mathematical techniques to justify ignoring this resistance in almost all cases. (one might, for example, treat the resistance of a wire as an infinitesimal quantity, and use techniques like those of [raiman, 86] to show that its effect is negligible.) But the computational costs of this approach are non-trivial, and become worse as more tiny but non-zero characteristics are found to be occasionally important. For example, a physical wire has non-zero capacitance and inductance; and it is possible to construct systems where these have non-negligible effects. If we include these as very small, but non-zero, quantities in our analysis of all models that contain wires, the effect is to add a second-order differential equation for each wire in the system, and then to remove it through a perturbation analysis. Pursuing this further, one would end up setting up Maxwell's equations, or Schrodinger's equations, or quantum electrodynamics for all space, and then throwing out all the lower-order terms. This is not feasible. Rather, reasoners will proceed by invoking the idealized assumption that a wire supports no voltage difference as a plausible inference at the time when a mathematical model is constructed from the given physical description, and replacing it by a more accurate assumption if necessary.
Thus, given a physical description that specifies that there is a wire between nodes A and B, we will prefer to model this by the equation VA VB if this is possible; if it is not, we will use a more detailed model.
The remainder of the paper studies theories that incorporate such inferences. Section 1 exhibits a simple example that is difficult to handle correctly if physical idealization is treated as a default rule in a non - monotonic logic. Section 2 show that probability theory can be made to give the right answer to the problem, but doing so involves some anomalies. Section 3 discusses the possibility of using deductive rather than defeasible inference. This can be made to work for simple microworlds, but it relies on an implicit notion of causal directionality that is, itself, hard to formalize. Section 4 discusses the relevance of these difficulties to physical prediction programs. Section 5 discusses a variety of examples where the failure of the idealization can be detected only over an extended interval, not at a single instant; such examples are even more difficult to analyze.
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Excerpt from Physical Idealization as Plausible Inference, Vol. 4
Let us make the simplifying assumption, for the moment, that the appropriate fix, here is to associate a small resistance with the wire. Thus, in most cases, we wish to approximate a wire as a short circuit; here, we wish to approximate it as a resistor of very low resistance. One way to accomplish this would be to change the basic model of a wire to be a small resistor; to apply this uniformly to all circuits; and then to use mathematical techniques to justify ignoring this resistance in almost all cases. (one might, for example, treat the resistance of a wire as an infinitesimal quantity, and use techniques like those of [raiman, 86] to show that its effect is negligible.) But the computational costs of this approach are non-trivial, and become worse as more tiny but non-zero characteristics are found to be occasionally important. For example, a physical wire has non-zero capacitance and inductance; and it is possible to construct systems where these have non-negligible effects. If we include these as very small, but non-zero, quantities in our analysis of all models that contain wires, the effect is to add a second-order differential equation for each wire in the system, and then to remove it through a perturbation analysis. Pursuing this further, one would end up setting up Maxwell's equations, or Schrodinger's equations, or quantum electrodynamics for all space, and then throwing out all the lower-order terms. This is not feasible. Rather, reasoners will proceed by invoking the idealized assumption that a wire supports no voltage difference as a plausible inference at the time when a mathematical model is constructed from the given physical description, and replacing it by a more accurate assumption if necessary.
Thus, given a physical description that specifies that there is a wire between nodes A and B, we will prefer to model this by the equation VA VB if this is possible; if it is not, we will use a more detailed model.
The remainder of the paper studies theories that incorporate such inferences. Section 1 exhibits a simple example that is difficult to handle correctly if physical idealization is treated as a default rule in a non - monotonic logic. Section 2 show that probability theory can be made to give the right answer to the problem, but doing so involves some anomalies. Section 3 discusses the possibility of using deductive rather than defeasible inference. This can be made to work for simple microworlds, but it relies on an implicit notion of causal directionality that is, itself, hard to formalize. Section 4 discusses the relevance of these difficulties to physical prediction programs. Section 5 discusses a variety of examples where the failure of the idealization can be detected only over an extended interval, not at a single instant; such examples are even more difficult to analyze.
About the Publisher
Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com
This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
Excerpt from Physical Idealization as Plausible Inference, Vol. 4
The analysis of physical systems almost always relies on idealized models of the objects involved. Any idealization, however, will be incorrect or insufficiently accurate some of the time. It seems reasonable, therefore, to view a physical idealization as a defeasible inference which can be withdrawn in the presence of contrary evidence. This talk discusses the consequences of such a view.
We focus on examples where a system may or may not go into a state where idealizations are violated, such as dropping a ball near an open switch connected across a battery. We show that:
1. Non-monotonic logics will try to enforce the idealization by supposing that the ball will miss the switch. This anomaly does not seem to be solvable by the kinds of techniques that have been applied to the Yale Shooting Problem, which it superficially resembles. We show that this problem is analogous to anomalies in non-monotonic logic that are time-independent.
2. A probabilistic analysis is possible, but it relies on independence assumptions that are hard to justify in general.
3. For completely specified systems, the rule "If the idealization gives solvable equations, then assumes that it holds" is, in fact, a monotonic system of inferences. It should therefore be possible to characterize this in a purely deductive theory. We show that this is, indeed, possible for simple cases, but can get messy in complex systems.
4. Programs that make physical predictions can avoid these problems by simply avoiding reasoning from the future to the past. Though most current programs observe this restriction, it seems likely that more powerful and general systems will have to violate it, and thus deal with this issue.
5. Finally, we look at dynamic systems where the idealization can be observed at any single instant, but it is inconsistent over extended intervals.
Reasoning about physical systems almost always relies on idealized models of the objects involved. Strings and pulleys are massless; springs obey Hooke slaw; solid objects are perfectly rigid, and so on [Addanki etal., 89]. Generally, analyses based on such idealizations are correct qualitatively and reasonably accurate quantitatively. (What constitutes reasonable accuracy depends both on the requirements of the task for which the analysis is being performed and on the availability of alternative models that are both more accurate and tractable. In practice, modellers often use idealizations that are known to be inaccurate, either because the next more accurate model is horribly complex, or because no more accurate model is known.)
Sometimes, however, simple idealizations give answers that are not adequate.
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This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
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Paperback. Condición: New. Print on Demand. This book delves into physical idealization as a plausible inference, examining the consequences of viewing a physical idealization as a defeasible inference. The author, an esteemed expert in the field, focuses on examples where a system may or may not deviate from an idealized state, such as a ball near an open switch connected to a battery. Through thought-provoking analysis, the book demonstrates that non-monotonic logics struggle to account for idealizations, while probabilistic analysis offers a partial solution but faces challenges in choosing independence assumptions. The author proposes a novel deductive theory to address these issues, highlighting instances where idealizations impose constraints over extended time periods. This significant work expands our understanding of physical idealization as a complex interplay of logic, probability, and time, offering valuable insights for researchers and practitioners in physical reasoning and artificial intelligence. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Nº de ref. del artículo: 9781330660706_0
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