This paper argues that every quantum system can be understood as a sufficiently general kind of stochastic process unfolding in an old-fashioned configuration space according to ordinary notions of probability. This argument is based on an exact correspondence between the class of “indivisible” stochastic processes and quantum theory. This new stochastic-quantum correspondence demotes the wave function from a primary ontological ingredient to a secondary mathematical tool and yields a deflationary account of exotic quantum phenomena, such as interference, (...) decoherence, entanglement, noncommutative observables, and wave-function collapse. At a more practical level, the stochastic-quantum correspondence leads to a novel reconstruction of quantum theory, alongside the Hilbert-space, path-integral, and quasiprobability representations, and also provides a framework for using Hilbert-space methods to formulate highly generic, non-Markovian types of stochastic dynamics, with potential applications throughout the sciences. (shrink)

Decision theorists widely accept a stochastic dominance principle: roughly, if a risky prospect A is at least as probable as another prospect B to result in something at least as good, then A is at least as good as B. Recently, philosophers have applied this principle even in contexts where the values of possible outcomes do not have the structure of the real numbers: this includes cases of incommensurable values and cases of infinite values. But in these contexts the (...) usual formulation of stochastic dominance is wrong. We show this with several counterexamples. Still, the motivating idea behind stochastic dominance is a good one: it is supposed to provide a way of applying dominance reasoning in the stochastic context of probability distributions. We give two new formulations of stochastic dominance that are more faithful to this guiding idea, and prove that they are equivalent. (shrink)

This paper introduces several new classes of mathematical structures that have close connections with physics and with the theory of dynamical systems. The most general of these structures, called generalized stochastic systems, collectively encompass many important kinds of stochastic processes, including Markov chains and random dynamical systems. This paper then states and proves a new theorem that establishes a precise correspondence between any generalized stochastic system and a unitarily evolving quantum system. This theorem therefore leads to a (...) new formulation of quantum theory, alongside the Hilbert-space, path-integral, and quasiprobability formulations. The theorem also provides a first-principles explanation for why quantum systems are based on the complex numbers, Hilbert spaces, linear-unitary time evolution, and the Born rule. In addition, the theorem suggests that by selecting a suitable Hilbert space, together with an appropriate choice of unitary evolution, one can simulate any generalized stochastic system on a quantum computer, thereby potentially opening up an extensive set of novel applications for quantum computing. (shrink)

With few exceptions, biological research dealing with stochasticity in molecular and cellular biology has focused on transcriptional processes (e.g., Elowitz et al. 2002; Lipniacki et al. 2006). Consequently, philosophical analyses have also centered on its role in transcription (e.g., Casali and Merlin 2020). Nonetheless, recent empirical evidence clearly shows that stochasticity is also pervasive in translation (e.g., Boersma et al. 2019). Focusing on time and a non-canonical case of translation (i.e., standard vs. alternative start codon selection), this paper aims to (...) disentangle a way in which stochasticity can intervene in models of this intracellular process. Having provided a definition of what we mean by stochasticity, first, we introduce two models of time in order to show where and how stochasticity can make a difference in the timing of translation processes. Second, we show how this difference can be biologically relevant for cell physiology. We conclude that, from an explanatory point of view, it is thus worth dissecting stochasticity when studying translation, gene expression and, more generally, biological processes at the molecular level. (shrink)

This paper addresses the problem of opaque sweetening and argues that one should use stochastic dominance in comparing lotteries even when dealing with incomplete orderings that allow for non-comparable outcomes.

The aim of the paper is to explicate the concept of causal independence between sets of factors and Reichenbach's screening-off-relation in probabilistic terms along the lines of Suppes' probabilistic theory of causality (1970). The probabilistic concept central to this task is that of conditional stochastic independence. The adequacy of the explication is supported by proving some theorems about the explicata which correspond to our intuitions about the explicanda.

Standard proofs of generalized Bell theorems, aiming to restrict stochastic, local hidden-variable theories for quantum correlation phenomena, employ as a locality condition the requirement of conditional stochastic independence. The connection between this and the no-superluminary-action requirement of the special theory of relativity has been a topic of controversy. In this paper, we introduce an alternative locality condition for stochastic theories, framed in terms of the models of such a theory (§2). It is a natural generalization of a (...) light-cone determination condition that is essentially equivalent to mathematical conditions that have been used to derive Bell inequalities in the deterministic case. Further, it is roughly equivalent to a condition proposed by Bell that, in one investigation, needed to be supplemented with a much stronger assumption in order to yield an inequality violated by some quantum mechanical predictions. It is shown here that this reflects a very general situation: from the proposed locality condition, even adding the strict anticorrelation condition and the auxiliary hypotheses needed to derive experimentally useful (and theoretically telling) inequalities, no Bell-type inequality is derivable. (These independence claims are the burden of §4.) A certain limitation on the scope of the proposed stochastic locality condition is exposed (§5), but it is found to be rather minor. The conclusion is thus supported that conditional stochastic independence, however reasonable on other grounds, is essentially stronger than what is required by the special theory.Our results stand in apparent contradiction with a class of derivations purporting to obtain generalized Bell inequalities from locality alone. It is shown in Appendix (B) that such proofs do not achieve their goal. This fits with our conclusion that generalized Bell theorems are not straightforward generalizations of theorems restricting deterministic hidden-variable theories, and that, in fact, such generalizations do not exist. This leaves open the possibility that a satisfactory, non-deterministic account of the quantum correlation phenomena can be given within the framework of the special theory. (shrink)

According to the stochastic-quantum correspondence, a quantum system can be understood as a stochastic process unfolding in an old-fashioned configuration space based on ordinary notions of probability and ‘indivisible’ stochastic laws, which are a non-Markovian generalization of the laws that describe a textbook stochastic process. The Hilbert spaces of quantum theory and their ingredients, including wave functions, can then be relegated to secondary roles as convenient mathematical appurtenances. In addition to providing an arguably more transparent way (...) to understand and modify quantum theory, this indivisible-stochastic formulation may lead to new possible applications of the theory. This paper initiates a deeper investigation into the conceptual foundations and structure of the stochastic-quantum correspondence, with a particular focus on novel forms of gauge invariance, dynamical symmetries, and Hilbert-space dilations. (shrink)

According to Stochastic Dominance, it is rationally obligatory to prefer one gamble to another if it gives you the same chances of getting final outcomes you prefer. According to Statewise Maximality, it is rationally permissible not to disprefer a gamble if it is guaranteed not to result in a final outcome you disprefer. These principles conflict in cases involving incomplete preferences, known as Opaque Sweetening cases. In this paper, we argue for Stochastic Dominance and against Statewise Maximality in (...) Opaque Sweetening cases. First, we rebut two standard arguments for statewise maximality, which we call the Argument from Full Information and the Argument from the Primacy of Final Outcomes. We then provide an argument for the verdict of Stochastic Dominance in Opaque Sweetening cases. This argument appeals to the principle of Transitivity, the Sure-Thing Principle, and the claim that stochastic reasoning is appropriate at least for choices which do not involve incomparability. (shrink)

A stochastic model is developed to describe behavioral changes by imitative pair interactions of individuals. ‘Microscopic’ assumptions on the specific form of the imitative processes lead to a stochastic version of the game dynamical equations, which means that the approximate mean value equations of these equations are the game dynamical equations of evolutionary game theory.The stochastic version of the game dynamical equations allows the derivation of covariance equations. These should always be solved along with the ordinary game (...) dynamical equations. On the one hand, the average behavior is affected by the covariances so that the game dynamical equations must be corrected for increasing covariances; otherwise they may become invalid in the course of time. On the other hand, the covariances are a measure of the reliability of game dynamical descriptions. An increase of the covariances beyond a critical value indicates a phase transition, i.e. a sudden change in the properties of the social system under consideration.The applicability and use of the equations introduced are illustrated by computational results for the social self-organization of behavioral conventions. (shrink)

A stochastic version of the Noether theorem is derived for systems under the action of external random forces. The concept of moment generating functional is employed to describe the symmetry of the stochastic forces. The theorem is applied to two kinds of random covariant forces. One of them generated in an electrodynamic way and the other is defined in the rest frame of the particle as a function of the proper time. For both of them, it is shown (...) the conservation of the mean value of a random drift momentum. The validity of the theorem makes clear that random systems can produce causal stochastic correlations between two faraway separated systems, that had interacted in the past. In addition possible connections of the discussion with the Ives Couder’s experimental results are remarked. (shrink)

It is shown that stochastic observables defined by an instrument need not, and generally do not, commute.

This article explores rationalizability issues for finite sets of observations of stochastic choice in the framework introduced by Bandyopadhyay et al. (Journal of Economic Theory, 84(1), 95–110, 1999). It is argued that a useful approach is to consider indirect preferences on budgets instead of direct preferences on commodity bundles. A new rationalizability condition for stochastic choices, “rationalizable in terms of stochastic orderings on the normalized price space” (rsop), is defined. rsop is satisfied if and only if there (...) exists a solution to a linear feasibility problem. The existence of a solution also implies rationalizability in terms of stochastic orderings on the commodity space. Furthermore it is shown that the problem of finding sufficiency conditions for binary choice probabilities to be rationalizable bears similarities to the problem considered here. (shrink)

The principle that rational agents should maximize expected utility or choiceworthiness is intuitively plausible in many ordinary cases of decision-making under uncertainty. But it is less plausible in cases of extreme, low-probability risk (like Pascal's Mugging), and intolerably paradoxical in cases like the St. Petersburg and Pasadena games. In this paper I show that, under certain conditions, stochastic dominance reasoning can capture most of the plausible implications of expectational reasoning while avoiding most of its pitfalls. Specifically, given sufficient background (...) uncertainty about the choiceworthiness of one's options, many expectation-maximizing gambles that do not stochastically dominate their alternatives "in a vacuum" become stochastically dominant in virtue of that background uncertainty. But, even under these conditions, stochastic dominance will not require agents to accept options whose expectational superiority depends on sufficiently small probabilities of extreme payoffs. The sort of background uncertainty on which these results depend looks unavoidable for any agent who measures the choiceworthiness of her options in part by the total amount of value in the resulting world. At least for such agents, then, stochastic dominance offers a plausible general principle of choice under uncertainty that can explain more of the apparent rational constraints on such choices than has previously been recognized. (shrink)

Stochastic dominance is a notion in expected-utility decision theory which has been developed to facilitate the analysis of risky or uncertain decision alternatives when the full form of the decision maker's von Neumann-Morgenstern utility function on the consequence space X is not completely specified. For example, if f and g are probability functions on X which correspond to two risky alternatives, then f first-degree stochastically dominates g if, for every consequence x in X, the chance of getting a consequence (...) that is preferred to x is as great under f as under g. When this is true, the expected utility of f must be as great as the expected utility of g.Most work in stochastic dominance has been based on increasing utility functions on X with X an interval on the real line. The present paper, following [1], formulates appropriate notions of first-degree and second-degree stochastic dominance when X is an arbitrary finite set. The only ‘structure’ imposed on X arises from the decision maker's preferences. It is shown how typical analyses with stochastic dominance can be enriched by applying the notion to convex combinations of probability functions. The potential applications of convex stochastic dominance include analyses of simple-majority voting on risky alternatives when voters have similar preference orders on the consequences. (shrink)

Models of choice over menus aim at capturing the effect of some behavioral or non-standard element of decision-making on the behavior of a single decision-maker. These models are usually compared with the standard model of choice over menus, in which the decision-maker chooses a menu whose best item is better than that of all other available ones. However, in many empirical settings such as experimental studies, choice data come from a population of decision-makers with possibly heterogeneous attitudes and tastes. This (...) heterogeneity can make the observed choices over menus stochastic. This fact calls for a stochastic characterization of models of choice over menus to be able to better compare and contrast different models empirically. In this paper, I do this task for the standard model, which would be an extension of the random utility model to the realm of choice over menus. In particular, I provide the necessary and sufficient conditions, i.e., axioms on choice data over menus for it to be consistent with a population of decision-makers each of whom behaves according to the standard model. The axioms that characterize the model are the axiom of revealed stochastic preferences over singletons and three rationality axioms. (shrink)

This work has two objectives. The first is to begin a mathematical formalism appropriate to treating particles which only interact with each otherindirectly due to hypothesized memory effects in a stochastic medium. More specifically we treat a situation in which a sequence of particles consecutively passes through a region (e.g., a measuring apparatus) in such a way that one particle leaves the region before the next one enters. We want to study a situation in which a particle may interact (...) with other particles that previously passed through the system via disturbances made in the region by these previous particles.Second, we apply the type of stochastic process appearing in this context to the stochastic interpretation of quantum mechanics to obtain a modified version of this interpretation. This version is free of many of the criticisms made against the stochastic interpretation of quantum mechanics. (shrink)

We first define a class of processes which we call regular quantum Markov processes. We next prove some basic results concerning such processes. A method is given for constructing quantum Markov processes using transition amplitude kernels. Finally we show that the Feynman path integral formalism can be clarified by approximating it with a quantum stochastic process.

The aim of this paper is to study the monotonicity properties with respect to the probability distribution of the state processes, of optimal decisions in bandit decision problems. Orderings of dynamic discrete projects are provided by extending the notion of stochastic dominance to stochastic processes.

I develop a notion of nonlinear stochastic integrals for hyperfinite Lévy processes and use it to find exact formulas for expressions which are intuitively of the form $\sum_{s=0}^t\phi(\omega,dl_{s},s)$ and $\prod_{s=0}^t\psi(\omega,dl_{s},s)$ , where l is a Lévy process. These formulas are then applied to geometric Lévy processes, infinitesimal transformations of hyperfinite Lévy processes, and to minimal martingale measures. Some of the central concepts and results are closely related to those found in S. Cohen’s work on stochastic calculus for processes (...) with jumps on manifolds, and the paper may be regarded as a reworking of his ideas in a different setting and with totally different techniques. (shrink)

Over the last 40 years or so, there has been an explosion of cultural evolution research in anthropology and archaeology. In each discipline, cultural evolutionists investigate how interactions between individuals translate into group level patterns, with the aim of explaining the diachronic dynamics and diversity of cultural traits. However, while much attention has been given to deterministic processes, we contend that current evolutionary accounts of cultural change are limited because they do not adopt a systematic stochastic approach. First, we (...) show that, in contrast with the intense debates in ecology and population genetics, the importance of stochasticity in evolutionary processes has generated little discussion in the sciences of cultural evolution to date. Second, we speculate on the reasons, both ideological and methodological, why that should be so. Third, we highlight the inadequacy of genetically-inspired stochastic models in the context of cultural evolution modelling, and ask which fundamental stochastic processes might be more relevant to take up. We conclude that the field of cultural evolution would benefit from a stochastic revolution. For that to occur, stochastic models ought to be developed specifically for cultural data and not through a copy-pasting of neutral models from population genetics or ecology. (shrink)

The replicator dynamics and Moran process are the main deterministic and stochastic models of evolutionary game theory. The models are connected by a mean-field relationship—the former describes the expected behavior of the latter. However, there are conditions under which their predictions diverge. I demonstrate that the divergence between their predictions is a function of standard techniques used in their analysis and of differences in the idealizations involved in each. My analysis reveals problems for stochastic stability analysis in a (...) broad class of games, demonstrates a novel domain of agreement between the dynamics, and indicates a broader moral for evolutionary modeling. (shrink)

The guiding idea of this work is that classical diffusion theory, being nonrelativistic, should be associated with nonrelativistic quantum mechanics. A study of classical diffusion leads to a generalization which should correspond to the relativistic domain. Actually, with a convenient choice of the basic constants, one sees the relativistic features (Lorentz contraction and covariant diffusion equation) emerge in the generalized process. This leads first to a derivation of the nonrelativistic and relativistic wave equations (and to a model of the Dirac (...) fluid); then to a better understanding of several relativistic aspects of quantum mechanics (spin connection with relativity and link of relativity with nonlocalization). No quantum mechanical forces are postulated: they arise as pseudo-forces in the course of the calculations. The physical significance of the stochastic model is examined and shown to give a pictorial description only in certain ideal situations, but to remove several conceptual difficulties. Remarks are presented on the role of idealization in microphysics. (shrink)

The connection with the quarks of the stochastic model proposed in the two preceding papers is studied; the slopes of the baryon trajectories are calculated with reference to the quarks. Suggestions are made for the interpretation of the model (quadratic or linear addition of the contributions to the mass, dependence of the decay on the quantum numbers of the hadrons involved, etc.) and concerning its link with the quarkonium model, which describes the mesons with charm or beauty. The controversial (...) question of the “subquantum level” is examined. (shrink)

I discuss various formulations of stochastic Einstein locality (SEL), which is a version of the idea of relativistic causality, that is, the idea that influences propagate at most as fast as light. SEL is similar to Reichenbach's Principle of the Common Cause (PCC), and Bell's Local Causality. My main aim is to discuss formulations of SEL for a fixed background spacetime. I previously argued that SEL is violated by the outcome dependence shown by Bell correlations, both in quantum mechanics (...) and in quantum field theory. Here I reassess those verdicts in the light of some recent literature which argues that outcome dependence does not violate the PCC. I argue that the verdicts about SEL still stand. Finally, I briefly discuss how to formulate relativistic causality if there is no fixed background spacetime. (shrink)

The paper extends the framework of outcomes in branching space-time (Kowalski and Placek [1999]) by assigning probabilities to outcomes of events, where these probabilities are interpreted either epistemically or as weighted possibilities. In resulting models I define the notion of common cause of correlated outcomes of a single event, and investigate which setups allow for the introduction of common causes. It turns out that a deterministic common cause can always be introduced, but (surprisingly) only special setups permit the introduction of (...) truly stochastic common causes. I analyse next the Bell-Aspect experiment and derive the Bell-CH inequalities. I observe that we postulate there not a common cause for outcomes of a single event but rather a common common cause that accounts for outcomes of many events, where 'events' mean 'measurements with (different) directions of polarization'. Since the inequalities are violated, I claim that no causal story can be told about the Bell correlations, where causality is subliminal and restricted by screening-off condition. Similarly, given certain intuitive principles, no deterministic story can be told about these correlations. (shrink)

The evolution of boundedly rational rules for playing normal form games is studied within stationary environments of stochastically changing games. Rules are viewed as algorithms prescribing strategies for the different normal form games that arise. It is shown that many of the “folk results” of evolutionary game theory, typically obtained with a fixed game and fixed strategies, carry over to the present environments. The results are also related to some recent experiments on rules and games.

This paper is devoted to the study of the notion of the phase-space representation of quantum theory in both the nonrelativisitic and the relativisitic cases. Then, as a derived concept, the stochastic phase space is introduced and its connections with fuzzy set theory and probabilistic topological (in particular, metric) spaces are discussed.

In this review we deal with open quantum systems within the Bohmian mechanics framework which has the advantage to provide a clear picture of quantum phenomena in terms of trajectories, originally in configuration space. The gradual decoherence process is studied from linear and nonlinear Schrödinger equations through Bohmian trajectories as well as by using the so-called quantum-classical transition differential equation through scaled trajectories. This transition is governed by a continuous parameter, the transition parameter, covering these two extreme open dynamical regimes. (...) Thus, two sources of decoherence of different nature are going to be considered. Several examples will be presented and discussed in order to illustrate the corresponding theory behind each case, namely: the so-called Brownian–Bohmian motion leading to quantum diffusion coefficients, dissipative diffraction in time, dissipative tunnelling for a parabolic barrier under the presence of an electric field and stochastic early arrivals for the same type of barrier. In order to simplify the notations and physical discussion, the theoretical developments will be carried out in one dimension throughout all this wok. One of the main goals is to analyze the gradual decoherence process existing in these open dynamical regimes in terms of trajectories, leading to a more intuitive way of understanding the underlying physics in order to gain new insights. (shrink)

In this article, we illustrate experimentally an important consequence of the stochastic component in choice behaviour which has not been acknowledged so far. Namely, its potential to produce ‘regression to the mean’ (RTM) effects. We employ a novel approach to individual choice under risk, based on repeated multiple-lottery choices (i.e. choices among many lotteries), to show how the high degree of stochastic variability present in individual decisions can distort crucially certain results through RTM effects. We demonstrate the point (...) in the context of a social comparison experiment. (shrink)

A theoretical framework for the reinforcement learning of aesthetic biases was recently proposed based on brain circuitries revealed by neuroimaging. A model grounded on that framework accounted for interesting features of human aesthetic biases. These features included individuality, cultural predispositions, stochastic dynamics of learning and aesthetic biases, and the peak-shift effect. However, despite the success in explaining these features, a potential weakness was the linearity of the value function used to predict reward. This linearity meant that the learning process (...) employed a value function that assumed a linear relationship between reward and sensory stimuli. Linearity is common in reinforcement learning in neuroscience. However, linearity can be problematic because neural mechanisms and the dependence of reward on sensory stimuli were typically nonlinear. Here, we analyze the learning performance with models including optimal nonlinear value functions. We also compare updating the free parameters of the value functions with the delta rule, which neuroscience models use frequently, vs. updating with a new Phi rule that considers the structure of the nonlinearities. Our computer simulations showed that optimal nonlinear value functions resulted in improvements of learning errors when the reward models were nonlinear. Similarly, the new Phi rule led to improvements in these errors. These improvements were accompanied by the straightening of the trajectories of the vector of free parameters in its phase space. This straightening meant that the process became more efficient in learning the prediction of reward. Surprisingly, however, this improved efficiency had a complex relationship with the rate of learning. Finally, the stochasticity arising from the probabilistic sampling of sensory stimuli, rewards, and motivations helped the learning process narrow the range of free parameters to nearly optimal outcomes. Therefore, we suggest that value functions and update rules optimized for social and ecological constraints are ideal for learning aesthetic biases. (shrink)

Studies on the development of cell populations are often based on results of the theory of stochastic birth- and death-processes (continuous or discrete (seee.g. references inVogel, Niewisch &Matioli (1969), in some cases, death may be interpreted not as actual death of the cell bute.g. as a recruitment of the cell considered into another cell compartment, etc.). It is usually assumed that the conditions for the development are homogeneous,i.e. that the probabilities of births and deaths are independent on the time. (...) However, in most situations, this assumption is not fulfilled (owing to the maturation and differentiation of cells, changes of the microenvironment, inducing factors, etc.). Then it is necessary to study the development of cell populations under non-homogeneous conditions. In this paper, some properties of appropriate birth- and death-processes under nonhomogeneous conditions are studied; formulae given in section 4 permit calculation of some characteristics describing the cell population size distribution at individual discrete epochs (at individual generations) during the development of the cell population considered. (shrink)

Traditionally, in the literature on the modelling of decision aids one notes the propensity to treat expected utility models and outranking relation models as rivals. It may be possible, however, to benefit from the use of both approaches in a risky decision context. Stochastic dominance conditions can be used to establish, for each criterion, the preferences of a decision maker and to characterise them by a concave or convex utility function.Two levels of complexity in preference elicitation, designated as clear (...) and unclear, are distinguished. Only in the case of unclear preferences is it potentially interesting to attempt to estimate the value function of the decision maker, thus obtaining his (her) preferences with a reduced number of questions. The number of questions that must be asked of the decision maker depends upon the level of the concordance threshold that he(she) requires in the construction of the outranking relations using the ELECTRE method. (shrink)

Scientists often think of the world as a dynamical system, a stochastic process, or a generalization of such a system. Prominent examples of systems are the system of planets orbiting the sun or any other classical mechanical system, a hydrogen atom or any other quantum–mechanical system, and the earth’s atmosphere or any other statistical mechanical system. We introduce a general and unified framework for describing such systems and show how it can be used to examine some familiar philosophical questions, (...) including the following: how can we define nomological possibility, necessity, determinism, and indeterminism; what are symmetries and laws; what regularities must a system display to make scientific inference possible; how might principles of parsimony such as Occam’s Razor help when we make such inferences; what is the role of space and time in a system; and might they be emergent features? Our framework is intended to serve as a toolbox for the formal analysis of systems that is applicable in several areas of philosophy. (shrink)

We define a semantics for conditionals in terms of stochastic graphs which gives a straightforward and simple method of evaluating the probabilities of conditionals. It seems to be a good and useful method in the cases already discussed in the literature, and it can easily be extended to cover more complex situations. In particular, it allows us to describe several possible interpretations of the conditional and to formalize some intuitively valid but formally incorrect considerations concerning the probabilities of conditionals (...) under these two interpretations. It also yields a powerful method of handling more complex issues. The stochastic graph semantics provides a satisfactory answer to Lewis’s arguments against the PC = CP principle, and defends important intuitions which connect the notion of probability of a conditional with the notion of conditional probability. It also illustrates the general problem of finding formal explications of philosophically important notions and applying mathematical methods in analyzing philosophical issues. (shrink)

This paper critically discusses an objection proposed by Nikolić against the naturalness of the stochastic dynamics implemented by the Bell-type quantum field theory, an extension of Bohmian mechanics able to describe the phenomena of particles creation and annihilation. Here I present: Nikolić’s ideas for a pilot-wave theory accounting for QFT phenomenology evaluating the robustness of his criticism, Bell’s original proposal for a Bohmian QFT with a particle ontology and the mentioned Bell-type QFT. I will argue that although Bell’s model (...) should be interpreted as a heuristic example showing the possibility to extend Bohm’s pilot-wave theory to the domain of QFT, the same judgement does not hold for the Bell-type QFT, which is candidate to be a promising possible alternative proposal to the standard version of quantum field theory. Finally, contra Nikolić, I will provide arguments in order to show how a stochastic dynamics is perfectly compatible with a Bohmian quantum theory. (shrink)

Assumptions of stochastic independence are crucial to statistical models in science. Under what circumstances is it reasonable to suppose that two events are independent? When they are not causally or logically connected, so the standard story goes. But scientific models frequently treat causally dependent events as stochastically independent, raising the question whether there are kinds of causal connection that do not undermine stochastic independence. This paper provides one piece of an answer to this question, treating the simple case (...) of two tossed coins with and without a midair collision. (shrink)

Stochastic independence has a complex status in probability theory. It is not part of the definition of a probability measure, but it is nonetheless an essential property for the mathematical development of this theory. Bayesian decision theorists such as Savage can be criticized for being silent about stochastic independence. From their current preference axioms, they can derive no more than the definitional properties of a probability measure. In a new framework of twofold uncertainty, we introduce preference axioms that (...) entail not only these definitional properties, but also the stochastic independence of the two sources of uncertainty. This goes some way towards filling a curious lacuna in Bayesian decision theory. (shrink)

Standard formulations of supervenience treat what is fixed by the base as a point-valued higher-level property. This presupposition becomes strained in scientific contexts in which laws constrain outcomes by fixing stable chance profiles—conditional probability measures—rather than single results. I propose stochastic supervenience as a conservative extension of deterministic supervenience: relative to a background set of laws $$\:L$$, base states determine a law-like kernel from $$\:B$$ to $$\:\varDelta\:\left(A\right)$$. To distinguish this framework from mere probabilistic correlation, I impose constraints ensuring that (...) the kernel is invariant across $$\:L$$ -worlds, non-degenerate, constant on $$\:L$$ -indiscernible base states, and subject to anti-trivialization conditions. Crucially, these conditions block “mere relabeling” reconstructions that render the dependence symmetric, and exclude treating non-Dirac structure as ignorance over $$\:L$$ -silent refinements. Deterministic supervenience is recovered as the Dirac boundary case, and I show that the dependence structure is preserved under coarse-graining when non-degeneracy is maintained. To connect the metaphysical proposal to scientific practice without reducing it to model-fitting, I introduce a compact diagnostic toolkit—normalized mutual information, a divergence spectrum with permutation baselines, body-tail comparisons for graded distributional multiple realization, and effective information under uniform interventions—to characterize the strength, structure, and intervention-salience of distributional dependence. The resulting framework preserves physicalist priority while making room for the law-governed uncertainty ubiquitous in the special sciences. (shrink)

Despite the extensive literature describing the somatic genetic alterations in cancer cells, the precise origins of cancer cells remain controversial. In this article, I suggest that the etiology of cancer and the generation of genetic instability in cancer cells should be considered in the light of recent findings on both the stochastic nature of gene expression and its regulation at tissue level. By postulating that gene expression is intrinsically probabilistic and that stabilization of gene expression arises by cellular interactions (...) in “morphogenetic fields”, development and cellular differentiation can be rethought in an evolutionary perspective. In particular, this article proposes that disruptions of cellular interactions are the initial source of abnormal gene expression in cancer cells. Consequently, cancer phenotypes such as genetic and epigenetic instabilities, and also the presence of cells with stem cell‐like properties, may result from inaccurate and aberrant patterns of gene expression generated by microenvironmental alterations. Finally, the therapeutic implications of this view are discussed. BioEssays 27:1277–1285, 2005. © 2005 Wiley Periodicals, Inc. (shrink)

Recently developed large language models (LLMs) perform surprisingly well in many language-related tasks, ranging from text correction or authentic chat experiences to the production of entirely new texts or even essays. It is natural to get the impression that LLMs know the meaning of natural language expressions and can use them productively. Recent scholarship, however, has questioned the validity of this impression, arguing that LLMs are ultimately incapable of understanding and producing meaningful texts. This paper develops a more optimistic view. (...) Drawing on classic externalist accounts of reference, it argues that LLM-generated texts meet the conditions of successful reference. This holds at least for proper names and so-called paradigm terms. The key insight here is that the LLM may inherit reference from its training-data through a reference-sustaining training mechanism. (shrink)

We formulate from first principles a theory of stochastic processes in configuration space. The fundamental equations of the theory are an equation of motion which generalizes Newton's second law and an equation which expresses the condition of conservation of matter. Two types of stochastic motion are possible, both described by the same general equations, but leading in one case to classical Brownian motion behavior and in the other to quantum mechanical behavior. The Schrödinger equation, which is derived here (...) with no further assumption, is thus shown to describe a specific stochastic process. It is explicitly shown that only in the quantum mechanical process does the superposition of probability amplitudes give rise to interference phenomena; moreover, the presence of dissipative forces in the Brownian motion equations invalidates the superposition principle. At no point are any special assumptions made concerning the physical nature of the underlying stochastic medium, although some suggestions are discussed in the last section. (shrink)

The stochastic scheme proposed in a previous paper as subjacent to quantum mechanics is analyzed in the light of the difficulties and criticisms encountered by similar attempts. It is shown that the limitation of the domain where the theory is valid gives a reply to the criticisms, but restricts its practical usefulness to the description of basic features. A stochastic approach of the hadron mass spectrum, allowing the scheme to emerge in the domain of experimental verification (to be (...) worked out in a later paper) is outlined. The model is found not to be in disagreement with Bell's argument opposed to hidden variables; a same origin is suggested for the difficulties encountered in both domains. The views proposed are compared with the Copenhagen interpretation: common points and divergences are analyzed. (shrink)

The stochastic phase-space solution of the particle localizability problem in relativistic quantum mechanics is reviewed. It leads to relativistically covariant probability measures that give rise to covariant and conserved probability currents. The resulting particle propagators are used in the formulation of stochastic geometries underlying a concept of quantum spacetime that is operationally based on stochastically extended quantum test particles. The epistemological implications of the intrinsic stochasticity of such quantum spacetime frameworks for microcausality, the EPR paradox, etc., are discussed.

Quantum stochastic models are developed within the framework of a measure entity. An entity is a structure that describes the tests and states of a physical system. A measure entity endows each test with a measure and equips certain sets of states as measurable spaces. A stochastic model consists of measurable realvalued function on the set of states, called a generalized action, together with measures on the measurable state spaces. This structure is then employed to compute quantum probabilities (...) of test outcomes. We characterize those measure entities that are isomorphic to a quantum probability space. We also show that stochastic models provide a phase space description of quantum mechanics and a realistic model of spin. (shrink)

The geometro-stochastic quantization of a gauge theory based on the (4,1)-de Sitter group is presented. The theory contains an intrinsic elementary length parameter R of geometric origin taken to be of a size typical for hadron physics. Use is made of a soldered Hilbert bundle ℋ over curved spacetime carrying a phase space representation of SO(4, 1) with the Lorentz subgroup related to a vierbein formulation of gravitation. The typical fiber of ℋ is a resolution kernel Hilbert space ℋ (...) $_{\bar \eta }^{(\rho )} $ constructed in terms of generalized coherent states $\bar \eta $ ρ related to the principal series of unitary irreducible representations of SO(4, 1), namely de Sitter horospherical waves for spinless particles characterized by the parameter ρ. The framework is, finally, extended to a quantum field-theoretical formalism by using bundles with Fock space fibers constructed from ℋ $_{\bar \eta }^{(\rho )} $. (shrink)

The thesis of physical supervenience is widely understood and endorsed as the weakest assertion that all facts are tethered to the physical facts. As an exercise in exploring the constitutive commitments of an ontic view of mechanistic explanation, I entertain a weaker tethering relation, stochastic physical supervenience, the possibility of which is suggested by analogy with the apparent failure of causal determinism in certain areas of physical science. Considering this possibility helps to clarify the constitutive commitments of mechanistic explanation (...) and to explore the motivations for accepting the PS thesis. (shrink)

In a small handful of papers in theoretical population genetics, John Gillespie (2000a, 2000b, 2001) argues that a new stochastic process he calls "genetic draft" is evolutionarily more significant than genetic drift. This case study of chance in evolution explores Gillespie's proposed stochastic evolutionary force and sketches the implications of Gillespie's argument for philosophers' explorations of genetic drift.

This position paper contests the stabilised academic reflex that frames large language models as stochastic parrots and, by extension, as epistemically irrelevant. The paper shifts the unit of analysis from the isolated model to the sociotechnical assemblage in which the model operates. Drawing on actor-network theory, cognitive semiotics, and research on joint cognitive systems, it argues that contemporary organisations already distribute cognition across artefacts, routines, and institutional constraints, so the question is not whether a model owns human-like understanding but (...) whether it functions as an effective mediator of knowledge and action. We integrate Paolucci’s work on humans as natural-born cyborgs and on meaning as enacted within semiotic environments to explain why human and artificial umwelten rarely intersect directly and why that mismatch is chiefly a property of biological embodiment rather than a defect of the model. We then mobilise resilience engineering and the WAx framework to describe how large language models compress complexity, accelerate conceptualisation, and support knowledge conversion across levels of work representation. The familiar catalogue of limitations is reinterpreted as a mirror of human under-specification, weak problem formulation, and institutional identity defence. The position advanced is deliberately polemical: in many modern sociotechnical systems, the most consequential bottleneck in human–model collaboration is often the human, and the emergent collaborative intelligence of the joint system can exceed that of traditional human-only teams. (shrink)