The foundations of Statistical Mechanics can be recovered almost in their entirety from the principle of maximum entropy. In this work we show that its non-equilibrium generalization, the principle of maximum caliber (Jaynes, Phys Rev 106:620–630, 1957), when applied to the unknown trajectory followed by a particle, leads to Newton’s second law under two quite intuitive assumptions (both the expected square displacement in one step and the spatial probability distribution of the particle are known at all times). (...) Our derivation explicitly highlights the role of mass as an emergent measure of the fluctuations in velocity (inertia) and the origin of potential energy as a manifestation of spatial correlations. According to our findings, the application of Newton’s equations is not limited to mechanical systems, and therefore could be used in modelling ecological, financial and biological systems, among others. (shrink)

In 1948 Van Lohuizen emphasized the importance of cooperation among all parties, and the need to establish continuous links between the scientific, aesthetic, and political dimensions of the planning process, so the necessary knowledge, talent, and insight can be accessed as if combined in one individual, to allow high caliber performance. Similar pleas have been made elsewhere, indicating special kinds of obstacles that affect such performance. In this article these obstacles are identified and interpreted as the result of an (...) ill-match between two approaches. According to the first, coordination and combination will be best when participant actors are modeled into well-defined roles, and their interactions coordinated via those roles. According to the second, differences should be made evident via the use of coordinating languages, leaving maximum freedom to and difference among participants, as voluntary users of those languages. Following the first approach, but not accepting its consequences as valued by the second approach, explains pleas like van Lohuizen’s. They can be fulfilled by explicating the methodology of the second approach. The article tries to provide both: the explanation and (part of the) methodology. (shrink)

We investigate uncertain reasoning with quantified sentences of the predicate calculus treated as the limiting case of maximum entropy inference applied to finite domains.

I begin with the definition of power, and find that it is finalistic inasmuch as work directs energy dissipation in the interests of some system. The maximum power principle of Lotka and Odum implies an optimal energy efficiency for any work; optima are also finalities. I advance a statement of the maximum entropy production principle, suggesting that most work of dissipative structures is carried out at rates entailing energy flows faster than those that would associate with maximum (...) power. This is finalistic in the sense that the out-of-equilibrium universe, taken as an isolated system, entrains work in the interest of global thermodynamic equilibration. I posit an evolutionary scenario, with a development on Earth from abiotic times, when promoting convective energy flows could be viewed as the important function of dissipative structures, to biotic times when the preservation of living dissipative structures was added to the teleology. Dissipative structures are required by the equilibrating universe to enhance local energy gradient dissipation. (shrink)

A special kind of maximum cuts in sequent derivations, actual maximum cuts, is defined. It is shown that (1) each actual maximum cut of a sequent derivation makes maximum segments in its natural deduction image, and (2) each maximum segment of a natural deduction derivation makes an actual maximum cut in its sequent image.

Categorical loudness scaling (CLS) measures provide useful information about an individual’s loudness perception across the dynamic range of hearing. A probability model of CLS categories has previously been described as a multi-category psychometric function (MCPF). In the study, a representative “catalog” of potential listener MCPFs was used in conjunction with maximum-likelihood estimation to derive CLS functions for participants with normal hearing and with hearing loss. The approach of estimating MCPFs for each listener has the potential to improve the accuracy (...) of the CLS measurements, particularly when a relatively low number of data points are available. The present study extends the MCPF approach by using Bayesian inference to select stimulus parameters that are predicted to yield maximum expected information (MEI) during data collection. The accuracy and reliability of the MCPF-MEI approach were compared to the standardized CLS measurement procedure (ISO16832:2006). A non-adaptive, fixed-level, paradigm served as a “gold-standard” for this comparison. The test time required to obtain measurements in the standard procedure is a major barrier to its clinical uptake. Test time was reduced from approximately 15 minutes to approximately 3 minutes with the MEI-adaptive procedure. Results indicated that the test-retest reliability and accuracy of the MCPF-MEI adaptive procedures were similar to the standardized CLS procedure. Computer simulations suggest that the reliability and accuracy of the MEI procedure were limited by intrinsic uncertainty of the listeners represented in the MCPF catalog. In other words, the MCPF provided insufficient predictive power to significantly improve adaptive-tracking efficiency under practical conditions. Concurrent optimization of both the MCPF catalog and the MEI-adaptive procedure have the potential to produce better results. Regardless of the adaptive-tracking method used in the CLS procedure, the MCPF catalog remains clinically useful for enabling maximum-likelihood determination of loudness categories. (shrink)

Two open questions of inductive reasoning are solved: (1) does the principle of maximum entropy (pme) give a solution to the obverse Majerník problem; and (2) is Wagner correct when he claims that Jeffrey’s updating principle (jup) contradicts pme? Majerník shows that pme provides unique and plausible marginal probabilities, given conditional probabilities. The obverse problem posed here is whether pme also provides such conditional probabilities, given certain marginal probabilities. The theorem developed to solve the obverse Majerník problem demonstrates that (...) in the special case introduced by Wagner pme does not contradict jup, but elegantly generalizes it and offers a more integrated approach to probability updating. (shrink)

This paper is a sequel to an earlier result of the authors that in making inferences from certain probabilistic knowledge bases the maximum entropy inference process, ME, is the only inference process respecting “common sense.” This result was criticized on the grounds that the probabilistic knowledge bases considered are unnatural and that ignorance of dependence should not be identified with statistical independence. We argue against these criticisms and also against the more general criticism that ME is representation dependent. In (...) a final section, however, we provide a criticism of our own of ME, and of inference processes in general, namely that they fail to satisfy compactness. (shrink)

There is widespread agreement that the European Union is presently suffering from a lack of social justice. Yet there is significant disagreement about what the relevant injustice consists in: Federalists believe the EU can only remedy its justice deficit through the introduction of direct interpersonal transfers between people living in separate states. Intergovernmentalists believe the justice-related purpose of the EU is to enable states to cooperate fairly, and to remain internally just and democratic in the face of increased global pressure (...) on welfare states. I suggest that despite their fundamental differences, many of the most reasonable and prominent philosophical accounts of social justice in the EU nonetheless converge in their institutional prescriptions. In particular, they may each serve as a justificatory basis for introducing the European social minimum, an EU-wide income support scheme. (shrink)

In this paper we deal with some new axiom schemes for Peano's Arithmetic that can substitute the classical induction, least-element, collection and strong collection schemes in the description of PA.

We formulate an elementary statistical game which captures the essence of some fundamental quantum experiments such as photon polarization and spin measurement. We explore and compare the significance of the principle of maximum Shannon entropy and the principle of minimum Fisher information in solving such a game. The solution based on the principle of minimum Fisher information coincides with the solution based on an invariance principle, and provides an informational explanation of Malus' law for photon polarization. There is no (...) solution based on the principle of maximum Shannon entropy. The result demonstrates the merits of Fisher information, and the demerits of Shannon entropy, in treating some fundamental quantum problems. It also provides a quantitative example in support of a general philosophy: Nature intends to hide Fisher information, while obeying some simple rules. (shrink)

Jaynes's maximum entropy principle (MEP) is analyzed by considering in detail a recent controversy. Emphasis is placed on the inductive logical interpretation of “probability” and the concept of “total knowledge.” The relation of the MEP to relative frequencies is discussed, and a possible realm of its fruitful application is noted.

I suggest that classical General Relativity in four spacetime dimensions incorporates a Principal of Maximal Tension and give arguments to show that the value of the maximal tension is $\frac{{c^4 }}{{4G}}$ . The relation of this principle to other, possibly deeper, maximal principles is discussed, in particular the relation to the tension in string theory. In that case it leads to a purely classical relation between G and the classical string coupling constant α′ and the velocity of light c which (...) does not involve Planck's constant. (shrink)

The principle of maximum entropy is a general method to assign values to probability distributions on the basis of partial information. This principle, introduced by Jaynes in 1957, forms an extension of the classical principle of insufficient reason. It has been further generalized, both in mathematical formulation and in intended scope, into the principle of maximum relative entropy or of minimum information. It has been claimed that these principles are singled out as unique methods of statistical inference that (...) agree with certain compelling consistency requirements. This paper reviews these consistency arguments and the surrounding controversy. It is shown that the uniqueness proofs are flawed, or rest on unreasonably strong assumptions. A more general class of inference rules, maximizing the so-called Re[acute ]nyi entropies, is exhibited which also fulfill the reasonable part of the consistency assumptions. (shrink)

Sometimes we receive evidence in a form that standard conditioning (or Jeffrey conditioning) cannot accommodate. The principle of maximum entropy (MAXENT) provides a unique solution for the posterior probability distribution based on the intuition that the information gain consistent with assumptions and evidence should be minimal. Opponents of objective methods to determine these probabilities prominently cite van Fraassen’s Judy Benjamin case to undermine the generality of maxent. This article shows that an intuitive approach to Judy Benjamin’s case supports maxent. (...) This is surprising because based on independence assumptions the anticipated result is that it would support the opponents. It also demonstrates that opponents improperly apply independence assumptions to the problem. (shrink)

This paper concerns the question of how to draw inferences common sensically from uncertain knowledge. Since the early work of Shore and Johnson (1980), Paris and Vencovská (1990), and Csiszár (1989), it has been known that the Maximum Entropy Inference Process is the only inference process which obeys certain common sense principles of uncertain reasoning. In this paper we consider the present status of this result and argue that within the rather narrow context in which we work this complete (...) and consistent mode of uncertain reasoning is actually characterised by the observance of just a single common sense principle (or slogan). (shrink)

This editorial explains the scope of the special issue and provides a thematic introduction to the contributed papers.

The inference systems proposed for solving SAT are unsound for solving MaxSAT and MinSAT, because they preserve satisfiability but not the minimum and maximum number of clauses that can be falsified, respectively. To address this problem, we first define a clause tableau calculus for MaxSAT and prove its soundness and completeness. We then define a clause tableau calculus for MinSAT and also prove its soundness and completeness. Finally, we define a complete clause tableau calculus for solving both MaxSAT and (...) MinSAT, in that the minimum number of generated empty clauses provides an optimal MaxSAT solution and the maximum number provides an optimal MinSAT solution. (shrink)

Objective Bayesian epistemology invokes three norms: the strengths of our beliefs should be probabilities, they should be calibrated to our evidence of physical probabilities, and they should otherwise equivocate sufficiently between the basic propositions that we can express. The three norms are sometimes explicated by appealing to the maximum entropy principle, which says that a belief function should be a probability function, from all those that are calibrated to evidence, that has maximum entropy. However, the three norms of (...) objective Bayesianism are usually justified in different ways. In this paper we show that the three norms can all be subsumed under a single justification in terms of minimising worst-case expected loss. This, in turn, is equivalent to maximising a generalised notion of entropy. We suggest that requiring language invariance, in addition to minimising worst-case expected loss, motivates maximisation of standard entropy as opposed to maximisation of other instances of generalised entropy. Our argument also provides a qualified justification for updating degrees of belief by Bayesian conditionalisation. However, conditional probabilities play a less central part in the objective Bayesian account than they do under the subjective view of Bayesianism, leading to a reduced role for Bayes’ Theorem. (shrink)

We prove that a form of the $Erd\H{o}s$ property (consistent with $V = L\lbrack H_{\omega_2}\rbrack$ and strictly weaker than the Weak Chang's Conjecture at ω1), together with Bounded Martin's Maximum implies that Woodin's principle $\psi_{AC}$ holds, and therefore 2ℵ0 = ℵ2. We also prove that $\psi_{AC}$ implies that every function $f: \omega_1 \rightarrow \omega_1$ is bounded by some canonical function on a club and use this to produce a model of the Bounded Semiproper Forcing Axiom in which Bounded Martin's (...) Maximum fails. (shrink)

In the sequent systems for exponential-free linear logic and BCK logic a procedure of elimination of maximum cuts, cuts which correspond to maximum segments from natural deduction derivations, will be presented.

Maximum-likelihood updating is a well-known approach for extending static ambiguity sensitive preferences to dynamic set-ups. This paper develops an example in which MLU induces an ambiguity averse maxmin expected utility decision-maker to prefer a bet on an ambiguous over a risky urn and be more willing to bet on the ambiguous urn compared to an subjective expected utility decision-maker. This is challenging, since prior to observing draws from the urns, the MEU decision-maker actually preferred the risky over the ambiguous (...) bet and was less willing to bet on the ambiguous urn than the SEU decision-maker. The identified switch in betting preferences is not due to a violation of dynamic consistency or consequentialism. Rather, it results from MLU’s selection of extreme priors, causing a violation of the stability of set inclusion over the course of the updating process. (shrink)

We isolate natural strengthenings of Bounded Martin’s Maximum which we call ${\mathsf{BMM}}^{*}$ and $A-{\mathsf{BMM}}^{*,++}$, and we investigate their consequences. We also show that if $A-{\mathsf{BMM}}^{*,++}$ holds true for every set of reals $A$ in $L$, then Woodin’s axiom $$ holds true. We conjecture that ${\mathsf{MM}}^{++}$ implies $A-{\mathsf{BMM}}^{*,++}$ for every $A$ which is universally Baire.