Rational analysis (Anderson 1990, 1991a) is an empiricalprogram of attempting to explain why the cognitive system isadaptive, with respect to its goals and the structure of itsenvironment. We argue that rational analysis has two importantimplications for philosophical debate concerning rationality. First,rational analysis provides a model for the relationship betweenformal principles of rationality (such as probability or decisiontheory) and everyday rationality, in the sense of successfulthought and action in daily life. Second, applying the program ofrational (...) analysis to research on human reasoning leads to a radicalreinterpretation of empirical results which are typically viewed asdemonstrating human irrationality. (shrink)

The proposed memory architecture by Barzykowski and Moulin is compelling, and could be improved by incorporating a rational analysis of the functional roles of involuntary autobiographical memory and déjà vu. Additionally, modeling these phenomena computationally would remove ambiguities from the proposal. We provide examples of past work that illustrate how the phenomena may be described more precisely.

How do people learn multisensory, or amodal, representations, and what consequences do these representations have for perceptual performance? We address this question by performing a rational analysis of the problem of learning multisensory representations. This analysis makes use of a Bayesian nonparametric model that acquires latent multisensory features that optimally explain the unisensory features arising in individual sensory modalities. The model qualitatively accounts for several important aspects of multisensory perception: (a) it integrates information from multiple sensory sources (...) in such a way that it leads to superior performances in, for example, categorization tasks; (b) its performances suggest that multisensory training leads to better learning than unisensory training, even when testing is conducted in unisensory conditions; (c) its multisensory representations are modality invariant; and (d) it predicts ‘‘missing” sensory representations in modalities when the input to those modalities is absent. Our rational analysis indicates that all of these aspects emerge as part of the optimal solution to the problem of learning to represent complex multisensory environments. (shrink)

Despite their success in describing and predicting cognitive behavior, the plausibility of so-called ‘rational explanations’ is often contested on the grounds of computational intractability. Several cognitive scientists have argued that such intractability is an orthogonal pseudoproblem, however, since rational explanations account for the ‘why’ of cognition but are agnostic about the ‘how’. Their central premise is that humans do not actually perform the rational calculations posited by their models, but only act as if they do. Whether or (...) not the problem of intractability is solved by recourse to ‘as if’ explanations critically depends, inter alia, on the semantics of the ‘as if’ connective. We examine the five most sensible explications in the literature, and conclude that none of them circumvents the problem. As a result, rational ‘as if’ explanations must obey the minimal computational constraint of tractability. (shrink)

Rational analysis is an influential but contested account of how probabilistic modeling can be used to construct non-mechanistic but self-standing explanatory models of the mind. In this paper, I disentangle and assess several possible explanatory contributions which could be attributed to rational analysis. Although existing models suffer from evidential problems that question their explanatory power, I argue that rational analysis modeling can complement mechanistic theorizing by providing models of environmental affordances.

While Bayesian models have been applied to an impressive range of cognitive phenomena, methodological challenges have been leveled concerning their role in the program of rational analysis. The focus of the current article is on computational impediments to probabilistic inference and related puzzles about empirical confirmation of these models. The proposal is to rethink the role of Bayesian methods in rational analysis, to adopt an independently motivated notion of rationality appropriate for computationally bounded agents, and to (...) explore broad conditions under which Bayesian agents would be rational. The proposal is illustrated with a characterization of costs inspired by thermodynamics. (shrink)

I agree with Oaksford & Chater (O&C) that human beings resemble Bayesian reasoners much more closely than ones engaging standard logic. However, I have many problems with their framework, which appears to be rooted in normative rather than ecological rationality. The authors also overstate everyday rationality and neglect to account for much relevant psychological work on reasoning.

At least two distinct modeling frameworks contribute to the view that mind and brain are Bayesian: Bayesian Rational Analysis (BRA) and Hierarchical Predictive Coding (HPC). What is the relative contribution of each, and how exactly do they relate? In order to answer this question, we compare the way in which these two modeling frameworks address different levels of analysis within Marr’s tripartite conception of explanation in cognitive science. Whereas BRA answers questions at the computational level only, many (...) HPC-theorists answer questions at the computational, algorithmic, and implementational levels simultaneously. Given that all three levels of analysis need to be addressed in order to explain a behavioral or cognitive phenomenon, HPC seems to deliver more complete explanations. Nevertheless, BRA is well-suited for providing a solution to the dark room problem, a major theoretical obstacle for HPC. A combination of the two approaches also combines the benefits of an embodied-externalistic approach to resolving the dark room problem with the idea of a persisting evidentiary border beyond which matters are out of cognitive reach. For this reason, the development of explanations spanning all three Marrian levels within the general Bayesian approach may require combining the BRA and HPC modeling frameworks. (shrink)

We report the results of a dual-task study in which participants performed a tracking and typing task under various experimental conditions. An objective payoff function was used to provide explicit feedback on how participants should trade off performance between the tasks. Results show that participants’ dual-task interleaving strategy was sensitive to changes in the difficulty of the tracking task and resulted in differences in overall task performance. To test the hypothesis that people select strategies that maximize payoff, a Cognitively Bounded (...) Rational Analysis model was developed. This analysis evaluated a variety of dual-task interleaving strategies to identify the optimal strategy for maximizing payoff in each condition. The model predicts that the region of optimum performance is different between experimental conditions. The correspondence between human data and the prediction of the optimal strategy is found to be remarkably high across a number of performance measures. This suggests that participants were honing their behavior to maximize payoff. Limitations are discussed. (shrink)

In this article, 41 models of covariation detection from 2 × 2 contingency tables were evaluated against past data in the literature and against data from new experiments. A new model was also included based on a limiting case of the normative phi‐coefficient under an extreme rarity assumption, which has been shown to be an important factor in covariation detection (McKenzie & Mikkelsen, 2007) and data selection (Hattori, 2002; Oaksford & Chater, 1994, 2003). The results were supportive of the new (...) model. To investigate its explanatory adequacy, a rational analysis using two computer simulations was conducted. These simulations revealed the environmental conditions and the memory restrictions under which the new model best approximates the normative model of covariation detection in these tasks. They thus demonstrated the adaptive rationality of the new model. (shrink)

Marr's levels of analysis—computational, algorithmic, and implementation—have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is (...) to push the notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call “resource-rational analysis.”. (shrink)

How can we study bounded rationality? We answer this question by proposing rational task analysis —a systematic approach that prevents experimental researchers from drawing premature conclusions regarding the rationality of agents. RTA is a methodology and perspective that is anchored in the notion of bounded rationality and aids in the unbiased interpretation of results and the design of more conclusive experimental paradigms. RTA focuses on concrete tasks as the primary interface between agents and environments and requires explicating essential (...) task elements, specifying rational norms, and bracketing the range of possible performance, before contrasting various benchmarks with actual performance. After describing RTA’s core components we illustrate its use in three case studies that examine human memory updating, multitasking behavior, and melioration. We discuss RTA’s characteristic elements and limitations by comparing it to related approaches. We conclude that RTA provides a useful tool to render the study of bounded rationality more transparent and less prone to theoretical confusion. (shrink)

The paper presents, in the synthetic way, the issue of the rationality of the tax system and taxation principles in relation to the clearly visible fiscal crisis in the 21st century caused by, among others, COVID-19 pandemic. The analysis which is theoretical (descriptive, comparative) was carried out by using tools indicated in the area of New Institutional Economics (NIE). Attention was devoted primarily to the importance of specific institutional arrangements, broadly understood as the “rules of the game” applicable in (...) the political and economic spheres, and related to the problems of public finances. Research has shown that the appropriate design of tax rules may contribute, to some extent, to limiting the fiscal crisis. Tax policy, and even more broadly, fiscal policy, may determine the formula in which the economic achievements regarding compliance with tax principles and fiscal rules can be implemented. What is primarily important is the legal framework (one of the most important formal institutions) within which state policy in the field of public finances should be implemented. (shrink)

I extend Jones & Love's (J&L's) critique of Bayesian models and evaluate the conceptual foundations on which they are built. I argue that: (1) the part of Bayesian models is scientifically trivial; (2) theory is a fiction that arises from an inappropriate programming metaphor; and (3) the real scientific problems lie outside Bayesian theorizing.

The term “synthetic biology” is a popular label of an emerging biotechnological field with strong claims to robustness, modularity, and controlled construction, finally enabling the creation of new organisms. Although the research community is heterogeneous, it advocates a common denominator that seems to define this field: the principles of rational engineering. However, it still remains unclear to what extent rational engineering—rather than “tinkering” or the usage of random based or non-rational processes—actually constitutes the basis for the techniques (...) of synthetic biology. In this article, we present the results of a quantitative bibliometric analysis of the realized extent of rational engineering in synthetic biology. In our analysis, we examine three issues: (1) We evaluate whether work at three levels of synthetic biology (parts, devices, and systems) is consistent with the principles of rational engineering. (2) We estimate the extent of rational engineering in synthetic biology laboratory practice by an evaluation of publications in synthetic biology. (3) We examine the methodological specialization in rational engineering of authors in synthetic biology. Our analysis demonstrates that rational engineering is prevalent in about half of the articles related to synthetic biology. Interestingly, in recent years the relative number of respective publications has decreased. Despite its prominent role among the claims of synthetic biology, rational engineering has not yet entirely replaced biotechnological methods based on “tinkering” and non-rational principles. (shrink)

This stimulating work takes the concept of 'rationality', a concept that more than any other is supposed to express the essence of what it means to be human, and submits it to a careful and penetrating analysis. The conclusions drawn often challenge those previously suggested by both philosophers and psychologists.

The transplant community has faced unprecedented challenges balancing risks of performing living donor transplants during the COVID-19 pandemic with harms of temporarily suspending these procedures. Decisions regarding postponement of living donation stem from its designation as an elective procedure, this despite that the Centers for Medicare and Medicaid Services categorise transplant procedures as tier 3b (high medical urgency—do not postpone). In times of severe resource constraints, health systems may be operating under crisis or contingency standards of care. In this manuscript, (...) the United Network for Organ Sharing Ethics Workgroup explores prioritisation of living donation where health systems operate under contingency standards of care and provide a framework with recommendations to the transplant community on how to approach living donation in these circumstances.To guide the transplant community in future decisions, this analysis suggests that: (1) living donor transplants represent an important option for individuals with end-stage liver and kidney disease and should not be suspended uniformly under contingency standards, (2) exposure risk to SARS-CoV-2 should be balanced with other risks, such as exposure risks at dialysis centres. Because many of these risks are not quantifiable, donors and recipients should be included in discussions on what constitutes acceptable risk, (3) transplant hospitals should strive to maintain a critical transplant workforce and avoid diverting expertise, which could negatively impact patient preparedness for transplant, (4) transplant hospitals should consider implementing protocols to ensure early detection of SARS-CoV-2 infections and discuss these measures with donors and recipients in a process of shared decision-making. (shrink)

Functional analysis rescued religion from the oblivion to which positiviste would have consigned it, by taking 'society' rather than the individual act as the unit of analysis. The history of functionalism has been a record of increasing concern with such holistic units as societies and social systems. One consequence of this shift away from social action (in the Weberian sense) is that the issue of rationality has become largely redundant. Yet the problem remains: How do we account for (...) 'contributions' to the social system in terms that make sense of the perspectives of social actors? An examination of unit actions as they are understood by social actors suggests that functionalism in fact incorporated many of the tenets held by positivists, and that it makes untenable (and implicit) assumptions concerning the 'objectivity' of the scientific observer. (shrink)

This article is an extension of the author’s previous work on this subject. Primarily it outlines the main directions of this mode of analysis and possible fields to which it could be applied. The first chapter demonstrates a specific method of understanding emotions. The second chapter examines the concept of emotions as a source of the specific modes of “internal” rationality of an agent. The third chapter isdevoted to a comparison between various emotions and the two basic intentional states (...) - belief and desire. The fourth chapter will present the instrumental typology of certain emotional concepts. The final chapter represents preliminary logical schema of the meanings of emotional concepts. (shrink)

This chapter contains section titled: Introduction A Characterization of Economic Analysis of Law Normativity Preference and Obligation Concluding Remarks Note References.

This article is an extension of the author’s previous work on this subject. Primarily it outlines the main directions of this mode of analysis and possible fields to which it could be applied. The first chapter demonstrates a specific method of understanding emotions. The second chapter examines the concept of emotions as a source of the specific modes of “internal” rationality of an agent. The third chapter isdevoted to a comparison between various emotions and the two basic intentional states (...) - belief and desire. The fourth chapter will present the instrumental typology of certain emotional concepts. The final chapter represents preliminary logical schema of the meanings of emotional concepts. (shrink)

Theories of rational decision making often abstract away from computational and other resource limitations faced by real agents. An alternative approach known as resource rationality puts such matters front and center, grounding choice and decision in the rational use of finite resources. Anticipated by earlier work in economics and in computer science, this approach has recently seen rapid development and application in the cognitive sciences. Here, the theory of rationality plays a dual role, both as a framework for (...) normative assessment and as a source of scientific hypotheses about how mental processes in fact work. The latter project, often called rational analysis, depends for its success on a fine-grained characterization of the computational problem facing a decision maker, which may in turn depend on realistic assumptions about what the relevant agent is like. As a consequence, resource rationality involves a delicate, but often fruitful interplay between the normative and the descriptive. (shrink)