It is a popular view thatpractical deliberation excludes foreknowledge of one's choice. Wolfgang Spohn and Isaac Levi have argued that not even a purely probabilistic self-predictionis available to thedeliberator, if one takes subjective probabilities to be conceptually linked to betting rates. It makes no sense to have a betting rate for an option, for one's willingness to bet on the option depends on the net gain from the bet, in combination with the option's antecedent utility, rather than on the offered (...) odds. And even apart from this consideration, assigning probabilities to the options among which one is choosing is futile since such probabilities could be of no possible use in choice. The paper subjects these arguments to critical examination and suggests that, appearances notwithstanding, practical deliberation need not crowd outself-prediction. (shrink)

In this paper it is argued that qualitative theories (Q-theories) can be used to describe the statistical structure of cross classified populations and that the notion of verisimilitude provides an appropriate tool for measuring the statistical adequacy of Q-theories. First of all, a short outline of the post-Popperian approaches to verisimilitude and of the related verisimilitudinarian non-falsificationist methodologies (VNF-methodologies) is given. Secondly, the notion of Q-theory is explicated, and the qualitative verisimilitude of Q-theories is defined. Afterwards, appropriate measures for the (...) statistical verisimilitude of Q-theories are introduced, so to obtain a clear formulation of the intuitive idea that the statistical truth about cross classified populations can be approached by falsified Q-theories. Finally, it is argued that some basic intuitions underlying VNF-methodologies are shared by the so-called prediction logic, developed by the statisticians and social scientists David K. Hildebrand, James D. Laing and Howard Rosenthal. (shrink)

A widely endorsed thesis in the philosophy of science holds that if evidence for a hypothesis was not known when the hypothesis was proposed, then that evidence confirms the hypothesis more strongly than would otherwise be the case. The thesis has been thought to be inconsistent with Bayesian confirmation theory, but the arguments offered for that view are fallacious. This paper shows how the special value of prediction can in fact be given Bayesian explanation. The explanation involves consideration of (...) the reliability of the method by which the hypothesis was discovered, and thus reveals an intimate connection between the 'logic of discovery' and confirmation theory. (shrink)

We present a logically detailed case-study of explanation and prediction in Newtonian mechanics. The case in question is that of a planet's elliptical orbit in the Sun's gravitational field. Care is taken to distinguish the respective contributions of the mathematics that is being applied, and of the empirical hypotheses that receive a mathematical formulation. This enables one to appreciate how in this case the overall logical structure of scientific explanation and prediction is exactly in accordance with the hypotheticodeductive (...) model. (shrink)

When we make a prediction we select, among the conceivable future descriptions of the world, those that appear to us to be most plausible. We capture this by means of two binary relations, ≺c and ≺p: if t1 and t2 are points in time, we interpret t1 ≺ct2 as sayingthat t2 is in the conceivable future of t1, while t1 ≺pt2 is interpreted to mean that t2 isin the predicted future of t1. Within a branching-time framework we propose the (...) following notion of “consistency of prediction”. Suppose that at t1 some future moment t2 is predicted to occur, then every moment t on the unique path from t1 to t2 should also be predicted at t1 and the prediction of t2 should continue to hold at every such t. A sound and complete axiomatization is provided. (shrink)

We present a logically detailed case-study of Darwinian evolutionary explanation. Special features of Darwin’s explanatory schema made it an unusual theoretical breakthrough, from the point of view of the philosophy of science. The schema employs no theoretical terms, and puts forward no theoretical hypotheses. Instead, it uses three observational generalizations—Variability, Heritability and Differential Reproduction—along with an innocuous assumption of Causal Efficacy, to derive Adaptive Evolution as a necessary consequence. Adaptive Evolution in turn, with one assumption of scale (‘Deep Time’), implies (...) the observational generalization of Adaptation. It is a fascinating methodological task to regiment the premises and make the reasoning both rigorous and clear. Doing so reveals how surprisingly small an amount of mathematics is needed in order to carry out the argument. The investigation also reveals the crucial role played by heritability, and how heritability itself admits of Darwinian explanation. (shrink)

The λ-continuum of inductive methods was derived from an assumption, called λ-condition, which says that the probability of finding an individual having property $x_{j}$ depends only on the number of observed individuals having property $x_{j}$ and on the total number of observed individuals. So, according to that assumption, all individuals with properties which are different from $x_{j}$ have equal weight with respect to that probability and, in particular, it does not matter whether any individual was observed having some property similar (...) to $x_{j}$ (the most complete proof of this result is presented in Carnap, 1980). The problem thus remained open to find some general condition, weaker than the λ-condition, which would allow for the derivation of probability functions which might be sensitive to similarity. Carnap himself suggested a weakening of the λ-condition which might allow for similarity sensitive probability functions (Carnap, 1980, p. 45) but he did not find the family of probability functions derivable from that principle. The aim of this paper is to present the family of probability functions derivable from Carnap's suggestion and to show how it is derived. In Section 1 the general problem of analogy by similarity in inductive logic is presented, Section 2 outlines the notation and the conceptual background involved in the proof, Section 3 gives the proof, Section 4 discusses Carnap's principle and the result, Section 5 is a brief review of the solutions which have previously been proposed. (shrink)

It is widely believed that if a piece of evidence for a theory was known at the time the theory was proposed, then it does not confirm the theory as strongly as it would if the evidence had been discovered after the theory was proposed. I shall call this view the predictivist thesis. Those who have endorsed it include Leibniz (1678), Huygens (1690, preface), Whewell (1847 vol. 2, p. 64f.), Peirce (1883), Duhem (1914, ch. II, §5), Popper (1965, p. 241f.), (...) Lakatos (1970, p. 123), and Kuhn (1977, p. 322). On the other hand, the thesis has been rejected by a number of philosophers, including Mill (1872 bk. III, ch. 14, §6), Keynes (1921, p. 305), Rosenkrantz (1977, p. 169f.), Horwich (1982, pp. 108-117) and Schlesinger (1987). Others, while not rejecting the predictivist thesis, nevertheless regard the justification of the thesis as problematic; these include Hempel (1966, p. 38) and Gardner (1982). (shrink)

The aim of the present research was to develop a difficulty model for logical reasoning problems involving complex ordered arrays used in the Graduate Record Examination. The approach used involved breaking down the problems into their basic cognitive elements such as the complexity of the rules used, the number of mental models required to represent the problem, and question type. Weightings for these different elements were derived from two experimental studies and from the reasoning literature. Based on these weights, difficulty (...) models were developed which were then tested against new data. The models had excellent predictive validity and showed the relative influence of rule based factors and factors relating to the number of underlying models. Different difficulty models were needed for different question types, suggesting that people used a variety of approaches and, at a wider level, that both mental models and mental rules may be used in reasoning. (shrink)

In recent years the problem of scientific prediction has attracted a constantly increasing number of researchers. The fact that a number of philosophers, logicians, and representatives of concrete disciplines have turned to investigating the nature of scientific prediction is first of all because of the needs of the development of scientific knowledge itself, as well as of industry. The rapid progress of the natural and the social sciences puts in the foreground the task of studying the internal regularities (...) of the process of acquisition of knowledge, the techniques and methods of research, and in particular, so very important a function of science as prediction. (shrink)

The prediction error minimization framework denotes a family of views that aim at providing a unified theory of perception, cognition, and action. In this paper, I discuss some of the theoretical limitations of PEM. It appears that PEM cannot provide a satisfactory explanation of motivated reasoning, as instantiated in phenomena such as self-deception, because its cognitive ontology does not have a separate category for motivational states such as desires. However, it might be thought that this objection confuses levels of (...) explanation. Self-deception is a personal level phenomenon, while PEM offers subpersonal explanations of psychological abilities. Thus, the paper examines how subpersonal explanations couched in the PEM framework can be thought of as related to personal level explanations underlying self-deception. In this regard, three views on the relation between personal and subpersonal explanations are investigated: the autonomist, the functionalist, and the co-evolutionary perspective. I argue that, depending on which view of the relation between the personal and subpersonal is adopted, the PEM paradigm faces a dilemma: either its explanatory ambitions should be reduced to the subpersonal domain, or it cannot provide a satisfactory account of motivated reasoning as instantiated in self-deception. (shrink)

The dynamic nature and increasing complexity of the construction industry have led to increased conflicts in construction projects. An accurate prediction of the outcome of a dispute resolution in courts could effectively reduce the number of disputes that would otherwise conclude by spending more money through litigation. This study aims to introduce a two-layered fuzzy logic model for predicting court decisions in construction contract disputes. 100 cases of construction contract disputes are selected from the courts of Iran. A (...) questionnaire survey is then conducted to extract a set of fuzzy rules for identifying important decision parameters and expert knowledge. Accordingly, a two-layered fuzzy logic-based decision-making architecture is proposed for the prediction model. Furthermore, the fuzzy system is trained based on 10-fold cross-validation. Analysis of results indicates that 51 out of the 100 cases are filed after the dissolution and termination of the contract show a significant impact of these clauses as the root cause in construction contract disputes. Our results present a proposed hierarchical fuzzy system that can correctly predict nearly 60% of the test data. Also, we demonstrate a methodology of using argument before ML to establish interpretable AI models. Based on our findings, a fuzzy model with a hierarchical structure may be used as a simple and efficient method for predicting court decisions in construction contract disputes. (shrink)

We take a logical approach to threshold models, used to study the diffusion of opinions, new technologies, infections, or behaviors in social networks. Threshold models consist of a network graph of agents connected by a social relationship and a threshold value which regulates the diffusion process. Agents adopt a new behavior/product/opinion when the proportion of their neighbors who have already adopted it meets the threshold. Under this diffusion policy, threshold models develop dynamically towards a guaranteed fixed point. We construct a (...) minimal dynamic propositional logic to describe the threshold dynamics and show that the logic is sound and complete. We then extend this framework with an epistemic dimension and investigate how information about more distant neighbors’ behavior allows agents to anticipate changes in behavior of their closer neighbors. Overall, our logical formalism captures the interplay between the epistemic and social dimensions in social networks. (shrink)

" The best way to predict the future is to invent it. —Alan Kay _1_ It is obvious that there are patterns of cultural change—evolution in the neutral sense—and any theory of cultural change worth more than a moment's consideration will have to be Darwinian in the minimal sense of being consistent with the theory of evolution by natural selection of Homo sapiens. —Daniel Dennett _2_ The future is here. It's just not widely distributed yet. —William Gibson _3_ It is (...) the magician's wand, by means of which he may summon into life whatever form and mould he pleases. —Charles Darwin commenting on the power of artificial selection _4_ " This article introduces an applied Theory of Evolution of Artificial Systems, called Directed Evolution. The theory is grounded in fifty years of research on Inventive Engineering known as TRIZ, which started in the former Soviet Union by G. Altshuller and continues today. The theory has generated a set of Patterns and Lines of Evolution that represent a compilation of trends that document strong, historically recurring tendencies in the development of manmade systems in general and technological systems in particular. Directed Evolution is the systematic applied-oriented process for “predicting” future generations of a system by inventing them along these evolutionary patterns. The current article introduces the theory, reflects on its basic underlying logic, and provides a broad historical context and intellectual justification for such an effort. It shows that the quest of DE theory and practice falls well within the boundaries of past pursuits to identify evolutionary patterns of complex systems and to use these patterns to control and manipulate possible futures of artificial systems. (shrink)

An implicit ambiguity in the field of prediction-based decision-making concerns the relation between the concepts of prediction and decision. Much of the literature in the field tends to blur the boundaries between the two concepts and often simply refers to ‘fair prediction’. In this paper, we point out that a differentiation of these concepts is helpful when trying to implement algorithmic fairness. Even if fairness properties are related to the features of the used prediction model, what (...) is more properly called ‘fair’ or ‘unfair’ is a decision system, not a prediction model. This is because fairness is about the consequences on human lives, created by a decision, not by a prediction. In this paper, we clarify the distinction between the concepts of prediction and decision and show the different ways in which these two elements influence the final fairness properties of a prediction-based decision system. As well as discussing this relationship both from a conceptual and a practical point of view, we propose a framework that enables a better understanding and reasoning of the conceptual logic of creating fairness in prediction-based decision-making. In our framework, we specify different roles, namely the ‘prediction-modeler’ and the ‘decision-maker,’ and the information required from each of them for being able to implement fairness of the system. Our framework allows for deriving distinct responsibilities for both roles and discussing some insights related to ethical and legal requirements. Our contribution is twofold. First, we offer a new perspective shifting the focus from an abstract concept of algorithmic fairness to the concrete context-dependent nature of algorithmic decision-making, where different actors exist, can have different goals, and may act independently. In addition, we provide a conceptual framework that can help structure prediction-based decision problems with respect to fairness issues, identify responsibilities, and implement fairness governance mechanisms in real-world scenarios. (shrink)

Conventional sacrificial moral dilemmas propose directly causing some harm to prevent greater harm. Theory suggests that accepting such actions (consistent with utilitarian philosophy) involves more reflective reasoning than rejecting such actions (consistent with deontological philosophy). However, past findings do not always replicate, confound different kinds of reflection, and employ conventional sacrificial dilemmas that treat utilitarian and deontological considerations as opposite. In two studies, we examined whether past findings would replicate when employing process dissociation to assess deontological and utilitarian inclinations independently. (...) Findings suggested two categorically different impacts of reflection: measures of arithmetic reflection, such as the Cognitive Reflection Test, predicted only utilitarian, not deontological, response tendencies. However, measures of logical reflection, such as performance on logical syllogisms, positively predicted both utilitarian and deontological tendencies. These studies replicate some findings, clarify others, and reveal opportunity for additional nuance in dual process theorist’s claims about the link between reflection and dilemma judgments. (shrink)

Predictive processing, an increasingly popular paradigm in cognitive sciences, has focused primarily on giving accounts of perception, motor control and a host of psychological phenomena, including consciousness. But higher cognitive processes, like conceptual thought, language, and logic, have received only limited attention to date and PP still stands disconnected from a huge body of research in those areas. In this thesis, I aim to address this gap and I attempt to go some way towards developing and defending a cognitive-computational (...) approach to higher cognition within the predictive processing paradigm. To test its explanatory potential, I apply it to a range of linguistic and conceptual phenomena. I proceed in three steps. First, I lay out an account of concepts and suggest how concepts are represented, how they can be context-sensitively processed, and how the apparent diversity of formats arise. Secondly, I propose how paradigmatic higher cognitive competencies, like language and logical reasoning, could fit into the PP picture. Thirdly, I apply the PP account of concepts and language to a range of linguistic-conceptual phenomena as test cases, namely: metaphor, the semantic paradox (specifically the Liar Paradox) and copredication. Finally, I discuss some challenges and objections to the PP framework as applied to higher cognition and in general. (shrink)

Connected vehicle fleets have formed significant component of industrial internet of things scenarios as part of Industry 4.0 worldwide. The number of vehicles in these fleets has grown at a steady pace. The vehicles monitoring with machine learning algorithms has significantly improved maintenance activities. Predictive maintenance potential has increased where machines are controlled through networked smart devices. Here, benefits are accrued considering uptimes optimization. This has resulted in reduction of associated time and labor costs. It has also provided significant increase (...) in cost benefit ratios. Considering vehicle fault trends in this research predictive maintenance problem is addressed through hybrid deep learning-based ensemble method (HDLEM). The ensemble framework which acts as predictive analytics engine comprises of three deep learning algorithms viz modified cox proportional hazard deep learning (MCoxPHDL), modified deep learning embedded semi supervised learning (MDLeSSL) and merged LSTM (MLSTM) networks. Both sensor as well as historical maintenance data are collected and prepared using benchmarking methods for HDLEM training and testing. Here, times between failures (TBF) modeling and prediction on multi-source data are successfully achieved. The results obtained are compared with stated deep learning models. This ensemble framework offers great potential towards achieving more profitable, efficient and sustainable vehicle fleet management solutions. This helps better telematics data implementation which ensures preventative management towards desired solution. The ensemble method's superiority is highlighted through several experimental results. (shrink)

Predictive processing framework has found wide applications in cognitive science and philosophy. It is an attractive candidate for a unified account of the mind in which perception, action, and cognition fit together in a single model. However, PP cannot claim this role if it fails to accommodate an essential part of cognition—conceptual thought. Recently, Williams argued that PP struggles to address at least two of thought’s core properties—generality and rich compositionality. In this paper, I show that neither necessarily presents a (...) problem for PP. In particular, I argue that because we do not have access to cognitive processes but only to their conscious manifestations, compositionality may be a manifest property of thought, rather than a feature of the thinking process, and result from the interplay of thinking and language. Pace Williams, both of these capacities, constituting parts of a complex and multifarious cognitive system, may be fully based on the architectural principles of PP. Under the assumption that language presents a subsystem separate from conceptual thought, I sketch out one possible way for PP to accommodate both generality and rich compositionality. (shrink)

Predictivists use the no miracle argument to argue that “novel” predictions are decisive evidence for theories, while mere accommodation of “old” data cannot confirm to a significant degree. But deductivists claim that since confirmation is a logical theory-data relationship, predicted data cannot confirm more than merely deduced data, and cite historical cases in which known data confirmed theories quite strongly. On the other hand, the advantage of prediction over accommodation is needed by scientific realists to resist Laudan’s criticisms of (...) the no miracle argument. So, if the deductivists are right, the most powerful argument for realism collapses. There seems to be an inescapable contradiction between these prima facie plausible arguments of predictivists and deductivists; but this puzzle can be solved by understanding what exactly counts as novelty, if novel predictions must support the no miracle argument, i.e., if they must be explainable only by the truth of theories. Taking my cues from the use-novelty tradition, I argue that (1) the predicted data must not be used essentially in building the theory or choosing the auxiliary assumptions. This is possible if the theory and its auxiliary assumptions are plausible independently of the predicted data, and I analyze the consequences of this requirement in terms of best explanation of diverse bodies of data. Moreover, the predicted data must be (2) a priori improbable, and (3) heterogeneous to the essentially used data. My proposed notion of novelty, therefore, is not historical, but functional. Hence, deductivists are right that confirmation is independent of time and of historical contingencies such as if the theorist knew a datum, used it, or intended to accommodate it. Predictivists, however, are right that not all consequences confirm equally, and confirmation is not purely a logical theory-data relation, as it crucially involves background epistemic conditions and the notion of best explanation. Conditions (1)–(3) make the difference between prediction and accommodation, and account for the confirming power of theoretical virtues such as non ad-hocness, non-fudging, non-overfitting, independence and consilience. I thus show that functional novelty (a) avoids the deductivist objections to predictivism, (b) is a gradual notion, in accordance with the common intuition that confirmation comes in degrees, and (c) supports the no miracle argument, so vindicating scientific realism. (shrink)

The central idea behind this paper is that presuppositions of soft triggers arise from the way our attention structures the informational content of a sentence. Some aspects of the information conveyed are such that we pay attention to them by default, even in the absence of contextual information. On the other hand, contextual cues or conversational goals can divert attention to types of information that we would not pay attention to by default. Either way, whatever we do not pay attention (...) to, be it by default, or in context, is what ends up presupposed by soft triggers. This paper attempts to predict what information in the sentence is likely to end up being the main point (i.e. what we pay attention to) and what information is independent from this, and therefore likely presupposed. It is proposed that this can be calculated by making reference to event times. The notion of aboutness used to calculate independence is based on that of Demolombe and Fariñas del Cerro (In: Holdobler S (ed) Intellectics and computational logic: papers in honor of Wolfgang Bibel, 2000). (shrink)

Considers that intuitive predictions follow a judgmental heuristic-representativeness. By this heuristic, people predict the outcome that appears most representative of the evidence. Consequently, intuitive predictions are insensitive to the reliability of the evidence or to the prior probability of the outcome, in violation of the logic of statistical prediction. The hypothesis that people predict by representativeness was supported in a series of studies with both naive and sophisticated university students. The ranking of outcomes by likelihood coincided with the (...) ranking by representativeness, and Ss erroneously predicted rare events and extreme values if these happened to be representative. The experience of unjustified confidence in predictions and the prevalence of fallacious intuitions concerning statistical regression are traced to the representativeness heuristic. (shrink)

An original study of the philosophical problems associated with inductive reasoning. Like most of the main questions in epistemology, the classical problem of induction arises from doubts about a mode of inference used to justify some of our most familiar and pervasive beliefs. The experience of each individual is limited and fragmentary, yet the scope of our beliefs is much wider; and it is the relation between belief and experience, in particular the belief that the future will in some respects (...) resemble the past and the unobserved the observed, which forms the subject of this book. Dr Blackburn's first aim is to state the problem of induction properly, to show that there does exist a genuine problem immune to the solutions in vogue at present, yet no tin principle insoluble. He gives an extended and original account of the concept of a reason and goes on to discuss prediction. In the end Dr Blackburn produces a rationale for belief in certain short-term predictions based on his reinterpretation of the classical principle of indifference. He claims that a justification for induction can be found along the lines he has suggested and must indeed be found there if anywhere. (shrink)

: In this paper I argue that belief in the greater confirmatory value of prediction over accommodation can best be understood as a function of the practice rather than the logic of science. Attempts to account for this asymmetry within the logic of science have revealed no non-arbitrary way to address the problem of underdetermination as it applies to prediction and thus have failed to account for the preference for prediction over accommodation on logical grounds. (...) Instead, I propose a model that not only justifies and explains this preference, but allows for a richer taxonomy of the types of evidential confirmation that are employed in scientific reasoning. (shrink)

Certain predictions are such that their accuracy can be affected by their dissemination, by their being believed and acted upon. Examples of such reflexive predictions are presented. Various approaches to the precise delineation of this category of predictions are explored, and a definition is proposed and defended. Next it is asked whether the possible reflexivity of predictions creates a serious methodological problem for the social sciences. A distinction between causal and logical reflexivity helps support a negative answer. Finally, we consider (...) the thesis that "this characteristic of predictions is peculiar to human affairs" (Merton), and an attempted rebuttal (Grunbaum). It is argued that Grunbaum's rebuttal is ineffective. (shrink)

Artificial intelligence is a general-purpose technology (GPT), term given to technologies that shape an entire era and reorient innovations by reconfiguring the economy’s logic and functioning and bringing in new business models. AI offers unprecedented opportunities and risks. The benefits of AI are extraordinary, as are its potential harms. Potential damage does not have the same degree of problematization, since the intensity and extent of the damage varies according to the domain and the object of application. To address the (...) scale of this challenge, regulation is necessary but not sufficient. Standards, unwritten codes of compliance and arbitration procedures, supervision and auditability, AI governance, international agreements, compliance with current local and global standards and laws. All of this needs to be integrated. Society seems to have no alternative to facing the challenges of at least mitigating the damage already identified and trying to predict future damage in advance. The purpose of this article is to encourage reflection regarding the main initiatives that are available to society to protect its citizens and organizations from the potential harm caused by AI models, vis-à-vis the technology’s own limits to act in ethical and legal compliance. (shrink)

We often need to have beliefs about things on which we are not experts. Luckily, we often have access to expert judgements on such topics. But how should we form our beliefs on the basis of expert opinion when experts conflict in their judgments? This is the core of the novice/2-expert problem in social epistemology. A closely related question is important in the context of policy making: how should a policy maker use expert judgments when making policy in domains in (...) which she is not herself an expert? This question is more complex, given the messy and strategic nature of politics. In this paper we argue that the prediction with expert advice framework from machine learning provides helpful tools for addressing these problems. We outline conditions under which we should expert PWEA to be helpful and those under which we should not expect these methods to perform well. (shrink)

This paper concerns exchangeable analogical predictions based on similarity relations between predicates, and deals with a restricted class of such relations. It describes a system of Carnapian λγ rules on underlying predicate families to model the analogical predictions for this restricted class. Instead of the usual axiomatic definition, the system is characterized with a Bayesian model that employs certain statistical hypotheses. Finally the paper argues that the Bayesian model can be generalized to cover cases outside the restricted class of similarity (...) relations. (shrink)

The accommodation of evidence has been argued to be associated with several methodological problems that should prompt evaluators to lower their confidence in the accommodative theory. Accommodators may overfit their model to data (Hitchcock and Sober, Br J Philos Sci 55(1):1–34, 2004. https://doi.org/10.1093/bjps/55.1.1), hunt for (spurious) associations between variables (Mayo, Error and the growth of experimental knowledge. University of Chicago Press, Chicago, 1996, pp 294–318), or ‘fudge’ their theory in the effort to accommodate a particular datum (Lipton, Inference to the (...) best explanation. Routledge, London, 2004, pp. 164–183). The converse of accommodation, novel prediction, has been offered as a solution. If theorists novelly predict empirical results rather than accommodate those results, the potential risks of accommodation are avoided, and the theory warrants greater confidence. This paper evaluates if the problems of accommodation justify a preference for novel prediction over accommodation for evaluators of a scientific theory. I argue that there is currently insufficient evidence to conclude that the problems of accommodation result in a predictivist advantage in theory confirmation. Taking into consideration the disadvantages of novel prediction and the advantages of accommodation, the impact of further evidential factors, and recent scientific evidence about the consequences of novel prediction and accommodation, novel prediction and accommodation appear roughly on a par, or accommodation is even superior in the current context. (shrink)

According to Hempel, all scientific explanations and predictions which are produced exclusively with deterministic laws must be deductive, in the sense that the explanandum or the prediction must be a logical consequence of the laws and the initial conditions in the explanans. This deducibility thesis has been attacked from several quarters. Some time ago Canfield and Lehrer presented a “refutation” of DT as applied to predictions, in which they tried to prove that “if the deductive reconstruction [DT for predictions] (...) were an adequate reconstruction, then scientific prediction would be impossible”. Their argument seems to have been uncontested except for an inconclusive rejoinder by Beard. Moreover, Stegmüller has recently argued that “it may turn out that all or at least most of the so-called deductive-nomological explanations are in truth inductive and not deductive arguments, in view of the difficulty which has been pointed out by Canfield and Lehrer”. It seems it would be worth investigating whether Canfield and Lehrer's argument is, indeed, correct. (shrink)

In this thesis I investigate the theoretical possibility of a universal method of prediction. A prediction method is universal if it is always able to learn from data: if it is always able to extrapolate given data about past observations to maximally successful predictions about future observations. The context of this investigation is the broader philosophical question into the possibility of a formal specification of inductive or scientific reasoning, a question that also relates to modern-day speculation about a (...) fully automatized data-driven science. I investigate, in particular, a proposed definition of a universal prediction method that goes back to Solomonoff and Levin. This definition marks the birth of the theory of Kolmogorov complexity, and has a direct line to the information-theoretic approach in modern machine learning. Solomonoff's work was inspired by Carnap's program of inductive logic, and the more precise definition due to Levin can be seen as an explicit attempt to escape the diagonal argument that Putnam famously launched against the feasibility of Carnap's program. The Solomonoff-Levin definition essentially aims at a mixture of all possible prediction algorithms. An alternative interpretation is that the definition formalizes the idea that learning from data is equivalent to compressing data. In this guise, the definition is often presented as an implementation and even as a justification of Occam's razor, the principle that we should look for simple explanations. The conclusions of my investigation are negative. I show that the Solomonoff-Levin definition fails to unite two necessary conditions to count as a universal prediction method, as turns out be entailed by Putnam's original argument after all; and I argue that this indeed shows that no definition can. Moreover, I show that the suggested justification of Occam's razor does not work, and I argue that the relevant notion of simplicity as compressibility is already problematic itself. (shrink)

Many philosophers have asserted that evolutionary theory is unfalsifiable. In this paper I refute these assertions by detailing some falsifiable predictions of the theory and the evidence used to test them. I then analyze both these predictions and evidence cited to support assertions of unfalsifiability in order to show both what type of predictions are possible and why it has been so difficult to spot them. The conclusion is that the apparent logical peculiarity of evolutionary theory is not a property (...) of evolutionary theory; it is a property of our human-sized perspective on evolutionary theory. (shrink)

No matter one’s wealth or social position, all are subject to the threats of natural hazards. Be it fire, flood, hurricane, earthquake, tornado, or drought, the reality of hazard risk is universal. In response, governments, non-profits, and the private sector all support research to study hazards. Each has a common end in mind: to increase the resilience of vulnerable communities. While this end goal is shared across hazards, the conception of how to get there can diverge considerably. The earthquake and (...) hurricane research endeavors in the US provide an illustrative contrast. The earthquake community sets out to increase resilience through a research process that simultaneously promotes both high quality and usable – preparedness-focused - science. In order to do so, the logic suggests that research must be collaborative, responsive, and transparent. Hurricane research, by contrast, largely promotes high quality science – predictions - alone, and presumes that usability should flow from there. This process is not collaborative, responsive, or transparent. Experience suggests, however, that the latter model – hurricane research - does not prepare communities or decision makers to use the high quality science it has produced when a storm does hit. The predictions are good, but they are not used effectively. Earthquake research, on the other hand, is developed through a collaborative process that equips decision makers to know and use hazards research knowledge as soon as an earthquake hits. The contrast between the two fields suggests that earthquake research is more likely to meet the end goal of resilience than is hurricane research, and thus that communities might be more resilient to hurricanes were the model by which research is funded and conducted to change. The earthquake research experience can provide lessons for this shift. This paper employs the Public Value Mapping (PVM) framework to explore these two divergent public value logics, their end results, and opportunities for improvement. (shrink)

Rid and Wendler propose the development of a Patient Preference Predictor (PPP), an actuarial model for predicting incapacitated patient’s life-sustaining treatment preferences across a wide range of end-of-life scenarios. An actuarial approach to end-of-life decision making has enormous potential, but transferring the logic of actuarial prediction to end-of-life decision making raises several conceptual complexities and logistical problems that need further consideration. Actuarial models have proven effective in targeted prediction tasks, but no evidence supports their effectiveness in the (...) kind of broad spectrum prediction task that is the proposed goal of the PPP. We argue that a more focused approach, targeting specific medical conditions and generating treatment predictions based on the preferences of individuals with actual disease experience, is both more firmly grounded in past research and is a more prudent initial strategy for exploring the efficacy of actuarial prediction in end-of-life decision making. (shrink)

This monograph analyzes Nicholas Rescher's system of pragmatic idealism. It also looks at his approach to prediction in science. Coverage highlights a prominent contribution to a central topic in the philosophy and methodology of science. The author offers a full characterization of Rescher's system of philosophy. She presents readers with a comprehensive philosophico-methodological analysis of this important work. Her research takes into account different thematic realms: semantic, logical, epistemological, methodological, ontological, axiological, and ethical. The book features three, thematic-parts: I) (...) General Coordinates, Semantic Features and Logical Components of Scientific Prediction; II) Predictive Knowledge and Predictive Processes in Rescher's Methodological Pragmatism; and III) From Reality to Values: Ontological Features, Axiological Elements, and Ethical Aspects of Scientific Prediction. This insightful analysis offers a critical reconstruction of Rescher's philosophy. The system he created is often characterized as pragmatic idealism that is open to some realist elements. He is a prominent representative of contemporary pragmatism who has made a great deal of contributions to the study of this topic. This area is crucial for science and it has been little considered in the philosophy of science. (shrink)

A key component of the susceptibility to cognitive biases is the ability to monitor for conflict between intuitively cued “heuristic” answers and logical principles. While there is evidence that pe...

We suggest a model that describes how counterfactuals are constructed and justified. The model can describe how counterfactual beliefs are updated given the unfolding of actual history. It also allows us to examine the use of counterfactuals in prediction, and to show that a logically omniscient reasoner gains nothing from using counterfactuals for prediction.

This unique compendium presents a comprehensive and self-contained theory of material development under imperfect information and its applications. The book describes new approaches to synthesis and selection of materials with desirable characteristics. Such approaches provide the ability of systematic and computationally effective analysis in order to predict composition, structure and related properties of new materials. The volume will be a useful advanced textbook for graduate students. It is also suitable for academicians and practitioners who wish to have fundamental models in (...) new material synthesis and selection. (shrink)

Abstract Evidence that supports a theory may be available to the scientist who constructs the theory and used as a guide to that construction, or it may only be discovered in the course of testing the theory. The central claim of this essay is that information about whether the evidence was accommodated or predicted affects the rational degree of confidence one ought to have in the theory. Only when the evidence is accommodated is there some reason to believe that the (...) theoretical system was ?fudged? to fit the evidence in a way that weakens support. This weakening is an objective matter, but not one that can be conclusively determined by examining the contents of the theory and its logical relationship to the evidence. Consequently, there is less reason to believe a theory on the basis of that evidence when it is known that the evidence was accommodated than there would be if it was known instead that the same evidence had been predicted. (shrink)