Our target article proposed that language production and comprehension are interwoven, with speakers making predictions of their own utterances and comprehenders making predictions of other people's utterances at different linguistic levels. Here, we respond to comments about such issues as cognitive architecture and its neural basis, learning and development, monitoring, the nature of forward models, communicative intentions, and dialogue.

The ability to process events in their temporal and sequential context is a fundamental skill made mandatory by constant interaction with a dynamic environment. Sequence learning studies have demonstrated that subjects exhibit detailed — and often implicit — sensitivity to the sequential structure of streams of stimuli. Current connectionist models of performance in the so-called Serial Reaction Time Task (SRT), however, fail to capture the fact that sequence learning can be based not only on sensitivity to the sequential associations between (...) successive stimuli, but also on sensitivity to the associations between successive responses, and on the predictive relationships that exist between these sequences of responses and their effects in the environment. In this paper, we offer an initial exploration of an alternative architecture for sequence learning, based on the principles of Forward Models. (shrink)

At the core of Pickering & Garrod's (P&G's) theory is a monitor that uses forward models. I argue that this account is challenged by neuropsychological findings and visual world eye-tracking data and that it has two conceptual problems. I propose that conflict monitoring avoids these issues and should be considered a promising alternative to perceptual loop and forward modeling theories.

Pickering & Garrod (P&G) consider the possibility that inner speech might be a product of forward production models. Here I consider the idea of inner speech as a forward model in light of empirical work from the past few decades, concluding that, while forward models could contribute to it, inner speech nonetheless requires activity from the implementers.

Open peer commentary on the article ““Black Box” Theatre: Second-Order Cybernetics and Naturalism in Rehearsal and Performance” by Tom Scholte. Upshot: My aim is to show that “truthful” acting that emerges through improvisation is equivalent to the development of mutual forward models in the actors. If these models match those of the audience members, this is perceived as “truthful.”.

The project of coordinating perception, comprehension, and motor control is an exciting one, but I found it hard to follow some of Pickering & Garrod's (P&G's) arguments as presented. Consequently, my comment is not so much a disagreement with P&G but a query about the logic of forward models: It is not clear how they are supposed to work, nor why they are needed in this (or many other) contexts, and toward that end I present an alternative idea.

The fundamental cognitive problem for active organisms is to decide what to do next in a changing environment. In this article, we analyze motor and action control in computational models that utilize reinforcement learning (RL) algorithms. In reinforcement learning, action control is governed by an action selection policy that maximizes the expected future reward in light of a predictive world model. In this paper we argue that RL provides a way to explicate the so-called action-oriented views of cognitive systems (...) in representational terms. (shrink)

The general applicability of forward models in brain function has previously been recognized. Grush's contribution centers largely on broadening the extent and scope of forward models. However, in his effort to expand and generalize, important distinctions may have been overlooked. A better grounding in the underlying physiology would have helped to illuminate such valuable differences and similarities.

A model policy for conscientious objection in medicine.

This paper explores the consequences of the theoretical forward activation enzymatic pathway A 0 A 1 A 2 A 3 where E 1 convents A 0 to A 1, E 2 converts A 1 to A 2 and E 3 converts A 2 to A 3. A 0, which is environmentally determined, also serves to activate (or modulate) the activity of E 3 in such a way as to keep the concentration of A 2 ([A 2]) constant at a (...) particular set-point value. For mathematical simplicity, first order rate kinetics are used where k 1, k 2 and k 3 are the rate constants for E 1, E 2, and E 3 respectively. It is shown that if k 3 is modulated appropriately so as keep [A 2] at the setpoint value with a changing upstream [A 0], then the modulation of k 3 must be anticipatory of the dynamics of the biochemical pathway. In other words, the rate of change of k 3, will be a function of [A 0], k 1, k 2, k 3, and the set-point value of [A 2]. If the modulation of k 3 does not perfectly model (anticipate) the reaction pathway of which it is a part, then the actual [A 2] will deviate from the set-point value. This type of anticipatory feed-forward activation may represent an important aspect of biological organization. (shrink)

The validity of assessment programs is increasingly important in higher education. Existing approaches to assessment are problematic because they eitherfail to provide timely feedback or have suspect measurement issues. We propose a feed-forward assessment model to help overcome these two limitations oftraditional assessment approaches.

This paper presents the results of a Catalan project in which an academic institution acted as a practitioner to promote corporate social responsibility (CSR) in small and medium-sized enterprises (SMEs). The project involved the establishment of a working network with intermediate organisations and the creation of specific tools for the purpose. The paper is set up as a case study, emphasising inclusion, representativity and legitimacy as key elements for the successful construction of a network to promote CSR in SMEs. It (...) underlines the assumptions behind the functioning of this network and the learning findings from this public–private initiative. Presented from a public policy perspective, the paper emphasises the need for coordination in terms of the growing number of initiatives fostering CSR in SMEs. It presents a brief account of the material results, focusing on the process of creating a consensus within the network. It opens up a path for future research, exploring how network management and leadership can be seen as key issues when talking about corporate social responsibility (CSR) promotion in SMEs. (shrink)

This paper presents the results of a Catalan project in which an academic institution acted as a practitioner to promote corporate social responsibility (CSR) in small and medium-sized enterprises (SMEs). The project involved the establishment of a working network with intermediate organisations and the creation of specific tools for the purpose. The paper is set up as a case study, emphasising inclusion, representativity and legitimacy as key elements for the successful construction of a network to promote CSR in SMEs. It (...) underlines the assumptions behind the functioning of this network and the learning findings from this public–private initiative. Presented from a public policy perspective, the paper emphasises the need for coordination in terms of the growing number of initiatives fostering CSR in SMEs. It presents a brief account of the material results, focusing on the process of creating a consensus within the network. It opens up a path for future research, exploring how network management and leadership can be seen as key issues when talking about corporate social responsibility (CSR) promotion in SMEs. (shrink)

In the target article, Bowers et al. dispute deep artificial neural network (ANN) models as the currently leading models of human vision without producing alternatives. They eschew the use of public benchmarking platforms to compare vision models with the brain and behavior, and they advocate for a fragmented, phenomenon-specific modeling approach. These are unconstructive to scientific progress. We outline how the Brain-Score community is moving forward to add new model-to-human comparisons to its community-transparent suite of benchmarks.

We affirm the dynamical systems approach taken by Feldman and Levin, but argue that a more mathematically rigorous and standard exposition of the model according to dynamical systems theory would greatly increase readability and testability. Such an explication would also have heuristic value, suggesting new variations of the model. We present one such variant, a new solution to the redundancy problem.

On the implementation aspect of the Islamization of knowledge programme, there were also suggestions that my paper should provide readers with Al-Faruqi's ...

Interactive theories of lexical retrieval in language production assume that activation cascades from earlier to later processing levels, and feeds back in the reverse direction. This commentary invites Pickering & Garrod (P&G) to consider whether cascading and feedback can be seen as a form of forwarding modeling within a hierarchical production system.

We provide eductive foundations for the concept of forward induction, in the class of games with an outside option. The formulation presented tries to capture in a static notion the rest point of an introspective process, achievable from some restricted preliminary beliefs. The former requisite is met by requiring the rest point to be a Nash equilibrium that yields a higher payoff than the outside option. With respect to the beliefs, we propose the Incentive Dominance Criterion. Players should consider (...) one action more likely than another whenever the former is better than getting the outside option for more conjectures over his rival's actions. We apply this model to the case where the subgame is a coordination game with a conflict between payoff dominance and risk dominance. Our results provide support for dominance solvability, but not for Van Damme's notion of forward induction. We show how the forward induction logic helps to select the Pareto dominant equilibrium. This is the case whenever player 1's act of giving up the outside option reverses the incentive dominance relations among 1's pure actions in the subgame. (shrink)

Mechanistic philosophy of science views a large part of scientific activity as engaged in modelling mechanisms. While science textbooks tend to offer qualitative models of mechanisms, there is increasing demand for models from which one can draw quantitative predictions and explanations. Casini et al. (Theoria 26(1):5–33, 2011) put forward the Recursive Bayesian Networks (RBN) formalism as well suited to this end. The RBN formalism is an extension of the standard Bayesian net formalism, an extension that allows for modelling the (...) hierarchical nature of mechanisms. Like the standard Bayesian net formalism, it models causal relationships using directed acyclic graphs. Given this appeal to acyclicity, causal cycles pose a prima facie problem for the RBN approach. This paper argues that the problem is a significant one given the ubiquity of causal cycles in mechanisms, but that the problem can be solved by combining two sorts of solution strategy in a judicious way. (shrink)

The energy sector contributes approximately two-thirds of global greenhouse gas emissions. In this context, the sector must adapt to new supply and demand networks for all future energy sources. The ongoing transformation in the European energy field is driven by the ambition of the European Union to reach the climate objectives set for 2030. The main actions are increasing renewable energy production, adapting transition fuels like natural gas to reduce emissions, improving energy efficiency across all economic sectors, prioritizing building, transportation, (...) and industry, developing Carbon Capture and Storage technologies, and ensuring universal access to clean and affordable energy. The significant changes envisaged in the energy sector to increase renewable energy production and consumption require improved integration and more use of predictive tools to support stakeholders' decision-making processes. This article presents a case study to assess the performance of predictive models based on a Feed-Forward Neural Network architecture that employ Root Mean Squared Propagation as their optimization function in terms of choosing the most appropriate activation function for this kind of data input and output. The training and testing phases of the models use data about building energy consumption. The lowest training time and Root Mean Square Error values were similar for Rectified Linear Unit and Tanh activation functions. The model with the Rectified linear Unit activation function performed best. (shrink)

Predictive processing theories are increasingly popular in philosophy of mind; such process theories often gain support from the Free Energy Principle (FEP)—a nor- mative principle for adaptive self-organized systems. Yet there is a current and much discussed debate about conflicting philosophical interpretations of FEP, e.g., repre- sentational versus non-representational. Here we argue that these different interpre- tations depend on implicit assumptions about what qualifies (or fails to qualify) as representational. We deploy the Free Energy Principle (FEP) instrumentally to dis- tinguish (...) four main notions of representation, which focus on organizational, struc- tural, content-related and functional aspects, respectively. The various ways that these different aspects matter in arriving at representational or non-representational interpretations of the Free Energy Principle are discussed. We also discuss how the Free Energy Principle may be seen as a unified view where terms that tradition- ally belong to different ontologies—e.g., notions of model and expectation versus notions of autopoiesis and synchronization—can be harmonized. However, rather than attempting to settle the representationalist versus non-representationalist debate and reveal something about what representations are simpliciter, this paper demon- strates how the Free Energy Principle may be used to reveal something about those partaking in the debate; namely, what our hidden assumptions about what represen- tations are—assumptions that act as sometimes antithetical starting points in this persistent philosophical debate. (shrink)

Lewis proposed to test the validity of a modal thesis by checking whether its possible-world translation is a theorem of counterpart theory. However, that criterion fails to validate many standard modal laws, thus raising doubts about the logical adequacy of the Lewisian framework. The present paper considers systems of counterpart theory of increasing strength and shows how each can be motivated by exhibiting a suitable intended model. In particular, perfect counterpart theory validates all the desired modal laws and therefore (...) provides a way out of the logical objection. Finally, a weakening of perfect counterpart theory is put forward as a response to some metaphysical objections. (shrink)

ABSTRACT How can imagination generate knowledge when its contents are voluntarily determined? Several philosophers have recently answered this question by pointing to the constraints that underpin imagination when it plays knowledge-generating roles. Nevertheless, little has been said about the nature of these constraints. In this paper, I argue that the constraints that underpin sensory imagination come from the structure of causal probabilistic generative models, a construct that has been highly influential in recent cognitive science and machine learning. I highlight several (...) attractions of this account, and I favourably contrast it with Peter Langland-Hassan’s account of sensory imagination in terms of the forward models exploited in sensorimotor control. (shrink)

The field of bioethics has deployed different models of justification for particular moral judgments. The best known models are those of deductivism, casuistry, and principlism (under one, rather limited interpretation). Each of these models, however, has significant difficulties that are explored in this essay. An alternative model, suggested by the work of Henry Richardson, is presented. It is argued that specified principlism is the most promising model of justification in bioethics. Keywords: casuistry, deductivism, ethical theories, intuition principlism, specified (...) principlism, specification CiteULike Connotea Del.icio.us What's this? (shrink)

ABSTRACT How can imagination generate knowledge when its contents are voluntarily determined? Several philosophers have recently answered this question by pointing to the constraints that underpin imagination when it plays knowledge-generating roles. Nevertheless, little has been said about the nature of these constraints. In this paper, I argue that the constraints that underpin sensory imagination come from the structure of causal probabilistic generative models, a construct that has been highly influential in recent cognitive science and machine learning. I highlight several (...) attractions of this account, and I favourably contrast it with Peter Langland-Hassan’s account of sensory imagination in terms of the forward models exploited in sensorimotor control. (shrink)

The central aim of science is to make sense of the world. To move forward as a community endeavor, sense-making must be systematic and focused. The question then is how do scientists actually experience the sense-making process? In this chapter we examine the “practice turn” in science studies and in particular how as a result of this turn scholars have come to realize that models are the “functional unit” of scientific thought and form the center of the reasoning/sense-making process. (...) This chapter will explore a context-dependent view of models and modeling in science. From this analysis we present a framework for delineating the different aspects of model-based reasoning and describe how this view can be useful in educational settings. This framework highlights how modeling supports and focuses scientific practice on sense-making. (shrink)

Biologists, climate scientists, and economists all rely on models to move their work forward. In this book, I explore the use of models in these and other fields to introduce readers to the various philosophical issues that arise in scientific modeling. I show that paying attention to models plays a crucial role in appraising scientific work. -/- After surveying a wide range of models from a number of different scientific disciplines, I demonstrate how focusing on models sheds light on (...) many perennial issues in philosophy of science and in philosophy in general. For example, reviewing the range of views on how models represent their targets introduces readers to the key issues in debates on representation, not only in science but in the arts as well. Also, standard epistemological questions are cast in new and interesting ways when we confront the question, "What makes for a good (or bad) model?". (shrink)

In this paper, we try to shed light on the ontological puzzle pertaining to models and to contribute to a better understanding of what models are. Our suggestion is that models should be regarded as a specific kind of signs according to the sign theory put forward by Charles S. Peirce, and, more precisely, as icons, i.e. as signs which are characterized by a similarity relation between sign (model) and object (original). We argue for this (1) by analyzing (...) from a semiotic point of view the representational relation which is characteristic of models. We then corroborate our hypothesis (2) by discussing the conceptual differences between icons, i.e. models, and indexical and symbolic signs and (3) by putting forward a general classification of all icons into three functional subclasses (images, diagrams, and metaphors). Subsequently, we (4) integratively refine our results by resorting to two influential and, as can be shown, complementary philosophy of science approaches to models. This yields the following result: models are determined by a semiotic structure in which a subject intentionally uses an object, i.e. the model, as a sign for another object, i.e. the original, in the context of a chosen theory or language in order to attain a specific end by instituting a representational relation in which the syntactic structure of the model, i.e. its attributes and relations, represents by way of a mapping the properties of the original, which hence are regarded as similar in a relevant manner. (shrink)

This study puts forward a rounder conceptual model for interpreting short and long-term effects of choice behavior. Kahneman’s (2011) distinction between cognitive processing System 1 and System 2 reflect the more rigorous distinction between Brief and Immediate and Extended and Elaborated Relational Responding. Specifically, we provide theoretical accounts and applied examples of how nudging, or the manipulation of environmental contingencies, works on the creation and modification of relational frames. The subset denominated educational nudges, or boosts, are particularly useful (...) towards their maintenance. We define and illustrate the fundamental mediating role of verbal behavior towards formulating rules, which inform and guide choice behavior over time. Furthermore, we suggest adopting the Implicit Relations Association Procedure to inform how coherent and immediate responding to new relational frames may be, whenever choices need be made. We provide empirical accounts of consumer behavior, stereotypy and prejudices, eating behavior, and overcoming cognitive biases. The conclusions depict a promising way forward towards an improved model for interpreting and overcoming human errors thanks to changes in the contingencies of choice behavior. (shrink)

We defend our multifactorial weighting model of the sense of agency and our critique of the comparator model against the critiques that have been brought forward by and . Building on the specification of our model that emerges from this response, we will suggest a distinct mechanism how weighting of different agency factors might work: internal and external agency cues are constantly weighted according to their reliability in a given situation. Thus, the weighting process underlying the (...) sense of agency might follow the principles of optimal cue integration. We review recent empirical evidence for this hypothesis, demonstrating that the multifactorial weighting model is not only testable, but has in fact already received first empirical support. (shrink)

What does it mean to be responsible for structural injustice? According to Iris Marion Young, the ongoing and socially embedded character of structural injustice imposes a future-oriented obligation to work with others toward creating remedial, institutional change. Young explains, ‘Political responsibility seeks less to reckon debts than to bring about results’ (Young, 2003, p. 13). This paper conceptually develops how the goal of remediation bears on responsibility in relation to structural injustice. Does the attribution of responsibility in this context call (...) upon individuals to simply do anything in efforts to affect progressive change? If not, then to what extent are these attributions of responsibility action guiding? On what basis do they direct agents to effectively intervene on relevant conditions and processes rather than act in ways that exacerbate the injustice? I explore the role of etiological explanation in the attribution and acceptance of corrective responsibility, which refers to diagnosis of the operative causation of unjust outcomes. After probing tensions within prominent models of corrective responsibility, I offer my own model attempting to resolve those issues. I argue the forward-looking nature of the call to participate in remedying social problems includes a demand for agents to do so in a way that is itself responsible. I theorize a framework of taking responsibility responsibly. This framework accounts for the moral difference between a conscientiously formulated program of remedial action and a quixotic exercise in reckless delusion. (shrink)

Model transfer refers to the observation that particular model structures are used across multiple distinct scientific domains. This paper puts forward an account to explain the inter-domain transfer of model structures. Central in the account is the role of validation criteria in determining whether a model is considered to be useful by practitioners. Validation criteria are points of reference to which model correctness for a particular purpose is assessed. I argue that validation criteria can (...) be categorized as being mathematical, theoretical or phenomenological in nature. Model transfer is explained by overlap in validation criteria between scientific domains. Particular emphasis is placed on overlap between phenomenological criteria. Overlap in phenomenological criteria can be explained through the notion of universal patterns. Universal patterns are abstract structures that can be made to refer to multiple distinct phenomena when coupled with phenomena-specific empirical content. I present the case study of the Yule Process, in which universal patterns play a crucial role in explaining model transfer. This paper provides an account of model transfer that stays close to modelling practice and expands existing accounts by introducing the notion of universal patterns. (shrink)

A serious crisis is identified in theories of neurocomputation, marked by a persistent disparity between the phenomenological or experiential account of visual perception and the neurophysiological level of description of the visual system. In particular, conventional concepts of neural processing offer no explanation for the holistic global aspects of perception identified by Gestalt theory. The problem is paradigmatic and can be traced to contemporary concepts of the functional role of the neural cell, known as the Neuron Doctrine. In the absence (...) of an alternative neurophysiologically plausible model, I propose a perceptual modeling approach, to model the percept as experienced subjectively, rather than modeling the objective neurophysiological state of the visual system that supposedly subserves that experience. A Gestalt Bubble model is presented to demonstrate how the elusive Gestalt principles of emergence, reification, and invariance can be expressed in a quantitative model of the subjective experience of visual consciousness. That model in turn reveals a unique computational strategy underlying visual processing, which is unlike any algorithm devised by man, and certainly unlike the atomistic feed-forward model of neurocomputation offered by the Neuron Doctrine paradigm. The perceptual modeling approach reveals the primary function of perception as that of generating a fully spatial virtual-reality replica of the external world in an internal representation. The common objections to this picture-in-the-head concept of perceptual representation are shown to be ill founded. Key Words: brain-anchored; Cartesian theatre; consciousness; emergence; extrinsic constraints; filling-in; Gestalt; homunculus; indirect realism; intrinsic constraints; invariance; isomorphism; multistability; objective phenomenology; perceptual modeling; perspective; phenomenology; psychophysical parallelism; psychophysical postulate; qualia; reification; representationalism; structural coherence. (shrink)

Knauff and Gazzo Castañeda (2022) object to using the term “new paradigm” to describe recent developments in the psychology of reasoning. This paper concedes that the Kuhnian term “paradigm” may be queried. What cannot is that the work subsumed under this heading is part of a new, progressive movement that spans the brain and cognitive sciences: Bayesian cognitive science. Sampling algorithms and Bayes nets used to explain biases in JDM can implement the Bayesian new paradigm approach belying any advantages of (...) mental models theory (MMT) at the algorithmic level. Moreover, this paper argues that new versions of MMT lack a computational level theory and questions the grounds for MMTs much-vaunted generality. The paper then examines common ground on the importance of small-scale models/simulations of the world and the importance of argumentation in the social domain rather than individual reasoning. Finally, the paper concludes that although there may be prospects for moving reasoning research forward in a more collective, collaborative manner, many disagreements remain to be resolved. (shrink)

Counterfactuals are inherently ambiguous in the sense that the same counterfactual may be true under one mode of counterfactualization but false under the other. Many have regarded the ambiguity of counterfactuals as consisting in the distinction between forward-tracking and backtracking counterfactuals. This is incorrect since the ambiguity persists even in cases not involving backtracking counterfactualization. In this paper, I argue that causal modeling semantics has the resources enough for accounting for the ambiguity of counterfactuals. Specifically, we need to distinguish (...) two types of causal manipulation, which I call “intervention” and “extrapolation” respectively. To intervene in a causal model M is to change M’s structural equations in some specific ways, while to extrapolate M is to change the value assignment of M’s variables in some specific ways. I argue that intervention and extrapolation offer a natural explanation for the ambiguity of counterfactuals. (shrink)

We examine two very different approaches to formalising real computation, commonly referred to as “Computable Analysis” and “the BSS approach”. The main models of computation underlying these approaches—bit computation and BSS, respectively—have also been put forward as appropriate foundations for scientific computing. The two frameworks offer useful computability and complexity results about problems whose underlying domain is an uncountable space. Since typically the problems dealt with in physical sciences, applied mathematics, economics, and engineering are also defined in uncountable domains, (...) it is fitting that we choose between these two approaches a foundational framework for scientific computing. However, the models are incompatible as to their results. What is more, the BSS model is highly idealised and unrealistic; yet, it is the de facto implicit model in various areas of computational mathematics, with virtually no problems for the everyday practice. This paper serves three purposes. First, we attempt to delineate what the goal of developing foundations for scientific computing exactly is. We distinguish between two very different interpretations of that goal, and on the separate basis of each one, we put forward answers about the appropriateness of each framework. Second, we provide an account of the fruitfulness and wide use of BSS, despite its unrealistic assumptions. Third, according to one of our proposed interpretations of the scope of foundations, the target domain of both models is a certain mathematical structure. In a clear sense, then, we are using idealised models to study a purely mathematical structure. The third purpose is to point out and explain this intriguing phenomenon and attempt to make connections with the typical case of idealised models of empirical domains. (shrink)