Arguments about the evolutionary function of phenomenal consciousness are beset by the problem of epiphenomenalism. For if it is not clear whether phenomenal consciousness has a causal role, then it is difficult to begin an argument for the evolutionary role of phenomenal consciousness. We argue that complexity arguments offer a way around this problem. According to evolutionary biology, the structural complexity of a given organ can provide evidence that the organ is an adaptation, even if nothing is known about the (...) causal role of the organ. Evidence from cognitive neuropsychology suggests that phenomenal consciousness is structurally complex in the relevant way, and this provides prima facie evidence that phenomenal consciousness is an adaptation. Furthermore, we argue that the complexity of phenomenal consciousness might also provide clues about the causal role of phenomenal consciousness. (shrink)

This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.

Recently, a number of philosophers of science have claimed that much explanation in the sciences, especially in the biomedical and social sciences, is mechanistic explanation. I argue the account of mechanistic explanation provided in this tradition has not been entirely satisfactory, as it has neglected to describe in complete detail the crucial causal structure of mechanistic explanation. I show how the interventionist approach to causation, especially within a structural equations framework, provides a simple and elegant account of the causal structure (...) of mechanisms. This account explains the many useful insights of traditional accounts of mechanism, such as Carl Craver's account in his book Explaining the Brain , but also helps to correct the omissions of such accounts. One of these omissions is the failure to provide an explicit formulation of a modularity constraint that plays a significant role in mechanistic explanation. One virtue of the interventionist/structural equations framework is that it allows for a simple formulation of a modularity constraint on mechanistic explanation. I illustrate the role of this constraint in the last section of the paper, which describes the form that mechanistic explanation takes in the computational, information-processing paradigm of cognitive psychology. (shrink)

Wants, preferences, and cares are physical things or events, not ideas or propositions, and therefore no chain of pure logic can conclude with a want, preference, or care. It follows that no pure-logic machine will ever want, prefer, or care. And its behavior will never be driven in the way that deliberate human behavior is driven, in other words, it will not be motivated or goal directed. Therefore, if we want to simulate human-style interactions with the world, we will need (...) to first understand the physical structure of goal-directed systems. I argue that all such systems share a common nested structure, consisting of a smaller entity that moves within and is driven by a larger field that contains it. In such systems, the smaller contained entity is directed by the field, but also moves to some degree independently of it, allowing the entity to deviate and return, to show the plasticity and persistence that is characteristic of goal direction. If all this is right, then human want-driven behavior probably involves a behavior-generating mechanism that is contained within a neural field of some kind. In principle, for goal directedness generally, the containment can be virtual, raising the possibility that want-driven behavior could be simulated in standard computational systems. But there are also reasons to believe that goal-direction works better when containment is also physical, suggesting that a new kind of hardware may be necessary. (shrink)

The functional complexity, or the number of functions, of organisms hasfigured prominently in certain theoretical and empirical work inevolutionary biology. Large-scale trends in functional complexity andcorrelations between functional complexity and other variables, such assize, have been proposed. However, the notion of number of functions hasalso been operationally intractable, in that no method has been developedfor counting functions in an organism in a systematic and reliable way.Thus, studies have had to rely on the largely unsupported assumption thatnumber of functions can be (...) measured indirectly, by using number ofmorphological, physiological, and behavioral parts as a proxy. Here, amodel is developed that supports this assumption. Specifically, the modelpredicts that few parts will have many functions overlapping in them, andtherefore the variance in number of functions per part will be low. If so,then number of parts is expected to be well correlated with number offunctions, and we can use part counts as proxies for function counts incomparative studies of organisms, even when part counts are low. Alsodiscussed briefly is a strategy for identifying certain kinds of parts inorganisms in a systematic way. (shrink)

Are there laws in evolutionary biology? Stephen J. Gould has argued that there are factors unique to biological theorizing which prevent the formulation of laws in biology, in contradistinction to the case in physics and chemistry. Gould offers the problem of complexity as just such a fundamental barrier to biological laws in general, and to Dollos Law in particular. But I argue that Gould fails to demonstrate: (1) that Dollos Law is not law-like, (2) that the alleged failure of Dollos (...) Law demonstrates why there cannot be laws in biological science, and (3) that complexity is a fundamental barrier to nomologicality. (shrink)

The importation of computational methods into biology is generating novel methodological strategies for managing complexity which philosophers are only just starting to explore and elaborate. This paper aims to enrich our understanding of methodology in integrative systems biology, which is developing novel epistemic and cognitive strategies for managing complex problem-solving tasks. We illustrate this through developing a case study of a bimodal researcher from our ethnographic investigation of two systems biology research labs. The researcher constructed models of metabolic and cell-signaling (...) pathways by conducting her own wet-lab experimentation while building simulation models. We show how this coupling of experiment and simulation enabled her to build and validate her models and also triangulate and localize errors and uncertainties in them. This method can be contrasted with the unimodal modeling strategy in systems biology which relies more on mathematical or algorithmic methods to reduce complexity. We discuss the relative affordances and limitations of these strategies, which represent distinct opinions in the field about how to handle the investigation of complex biological systems. (shrink)

The goal of this paper is to encourage a reconfiguration of the discussion about typology in biology away from the metaphysics of essentialism and toward the epistemology of classifying natural phenomena for the purposes of empirical inquiry. First, I briefly review arguments concerning ‘typological thinking’, essentialism, species, and natural kinds, highlighting their predominantly metaphysical nature. Second, I use a distinction between the aims, strategies, and tactics of science to suggest how a shift from metaphysics to epistemology might be accomplished. Typological (...) thinking can be understood as a scientific tactic that involves representing natural phenomena using idealizations and approximations, which facilitates explanation, investigation, and theorizing via abstraction and generalization. Third, a variety of typologies from different areas of biology are introduced to emphasize the diversity of this representational reasoning. One particular example is used to examine how there can be epistemological conflict between typology and evolutionary analysis. This demonstrates that alternative strategies of typological thinking arise due to the divergent explanatory goals of researchers working in different disciplines with disparate methodologies. I conclude with several research questions that emerge from an epistemological reconfiguration of typology. (shrink)

Scientific explanation is a perennial topic in philosophy of science, but the literature has fragmented into specialized discussions in different scientific disciplines. An increasing attention to scientific practice by philosophers is (in part) responsible for this fragmentation and has put pressure on criteria of adequacy for philosophical accounts of explanation, usually demanding some form of pluralism. This commentary examines the arguments offered by Fagan and Woody with respect to explanation and understanding in scientific practice. I begin by scrutinizing Fagan's concept (...) of collaborative explanation, highlighting its distinctive advantages and expressing concern about several of its assumptions. Then I analyze Woody's attempt to reorient discussions of scientific explanation around functional considerations, elaborating on the wider implications of this methodological recommendation. I conclude with reflections on synergies and tensions that emerge when the two papers are juxtaposed and how these draw attention to critical issues that confront ongoing philosophical analyses of scientific explanation. (shrink)

In 1958, Francis Crick distinguished the flow of information from the flow of matter and the flow of energy in the mechanism of protein synthesis. Crick’s claims about information flow and coding in molecular biology are viewed from the perspective of a new characterization of mechanisms and from the perspective of information as holding a key to distinguishing work in molecular biology from that of biochemistry in the 1950s–1970s . Flow of matter from beginning to end does not occur in (...) the protein synthesis mechanism; flow of information does. The flow of information and coding in molecular biological mechanisms are distinguished, on the one hand, from formal information theory, and, on the other, from information as used in cognitive neuroscience, where information and representation are often coupled. (shrink)

Ecological communities are seldom, if ever, biological individuals. They lack causal boundaries as the populations that constitute communities are not congruent and rarely have persistent functional roles regulating the communities’ higher-level properties. Instead we should represent ecological communities indexically, by identifying ecological communities via the network of weak causal interactions between populations that unfurl from a starting set of populations. This precisification of ecological communities helps identify how community properties remain invariant, and why they have robust characteristics. This respects the (...) diversity and aggregational nature of these complex systems while still vindicating them as units worthy of investigation. (shrink)

Besides mechanistic explanations of phenomena, which have been seriously investigated in the last decade, biology and ecology also include explanations that pinpoint specific mathematical properties as explanatory of the explanandum under focus. Among these structural explanations, one finds topological explanations, and recent science pervasively relies on them. This reliance is especially due to the necessity to model large sets of data with no practical possibility to track the proper activities of all the numerous entities. The paper first defines topological explanations (...) and then explains why topological explanations and mechanisms are different in principle. Then it shows that they are pervasive both in the study of networks—whose importance has been increasingly acknowledged at each level of the biological hierarchy—and in contexts where the notion of selective neutrality is crucial; this allows me to capture the difference between mechanisms and topological explanations in terms of practical modelling practices. The rest of the paper investigates how in practice mechanisms and topologies are combined. They may be articulated in theoretical structures and explanatory strategies, first through a relation of constraint, second in interlevel theories, or they may condition each other. Finally, I explore how a particular model can integrate mechanistic informations, by focusing on the recent practice of merging networks in ecology and its consequences upon multiscale modelling. (shrink)

Papers in experimental philosophy rarely offer an account of what it would take to reveal a philosophically significant effect. In part, this is because experimental philosophers tend to pay insufficient attention to the hierarchy of models that would be required to justify interpretations of their data; as a result, some of their most exciting claims fail as explanations. But this does not impugn experimental philosophy. My aim is to show that experimental philosophy could be made more successful by developing, articulating, (...) and advancing plausible models of the data that are collected and the analyses that are employed. (shrink)

If one investigates a process that has several causes but assumes that it has only one cause, one risks ruling out important causal factors. Three mechanisms account for this mistake: either the significance of the single cause under test is masked by noise contributed by the unsuspected and uncontrolled factors, or the process appears only when two or more causes interact, or the process appears when there are present any of a number of sufficient causes which are not mutally exclusive. (...) In ecology and evolutionary biology, experiments usually test single factor hypotheses, and many scientists apparently believe that hypotheses incorporating several factors are so much more difficult to test that to do so would not be practical. We discuss several areas in ecology and evolutionary biology in which the presupposition of simple causation has apparently impeded progress. We also examine a more mature field, the study of atherosclerosis, in which single factor studies did significantly delay progress towards understanding what now appears to be a multifactor process. The problem has three solutions: either factorial experiments, dynamic models that make quantitative predictions, response-surface methods, or all three. In choosing a definition for ‘cause’, we make a presupposition that profoundly influences subsequent observations and experimental designs. Alternative definitions of causation should be considered as contributing to potential cures for research problems. (shrink)

The relation between method, concept and theory in science is complicated. I seek to shed light on that relation by considering an instance of it in systematics: The additional challenges phylogeneticists face when reconstructing phylogeny not at a single level, but simultaneously at multiple levels of the hierarchy. How does this complicate the task of phylogenetic inference, and how might it inform and shape the conceptual foundations of phylogenetics? This offers a lens through which the interplay of method, theory and (...) concepts may be understood in systematics, which, in turn, provides data for a more general account. (shrink)

I spell out and update the individuality thesis, that species are individuals, and not classes, sets, or kinds. I offer three complementary presentations of this thesis. First, as a way of resolving an inconsistent triad about natural kinds; second, as a phylogenetic systematics theoretical perspective; and, finally, as a novel recursive account of an evolved character. These approaches do different sorts of work, serving different interests. Presenting them together produces a taxonomy of the debates over the thesis, and isolates ways (...) it has been productive. This goes to the larger point of this paper: a defense of the individuality thesis in terms of its utility, and an update of it in light of recent theoretical developments and empirical work in biology. (shrink)

We present two case studies from contemporary biology in which we observe conflicts between established and emerging approaches. The first case study discusses the relation between molecular biology and systems biology regarding the explanation of cellular processes, while the second deals with phylogenetic systematics and the challenge posed by recent network approaches to established ideas of evolutionary processes. We show that the emergence of new fields is in both cases driven by the development of high-throughput data generation technologies and the (...) transfer of modeling techniques from other fields. New and emerging views are characterized by different philosophies of nature, i.e. by different ontological and methodological assumptions and epistemic values and virtues. This results in a kind of conflict we call “epistemic competition” that manifests in two ways: On the one hand, opponents engage in mutual critique and defense of their fundamental assumptions. On the other hand, they compete for the acceptance and integration of the knowledge they provide by a broader scientific community. Despite an initial rhetoric of replacement, the views as well as the respective audiences come to be seen as more clearly distinct during the course of the debate. Hence, we observe—contrary to many other accounts of scientific change—that conflict results in the formation of new niches of research, leading to co-existence and perceived complementarity of approaches. Our model thus contributes to the understanding of the pluralization of the scientific landscape. (shrink)

Even though complexity is a concept that is ubiquitously used by biologists and philosophers of biology, it is rarely made precise. I argue that a clarification of the concept is neither trivial nor unachievable, and I propose a unifying framework based on the technical notion of “effective complexity” that allows me to do justice to conflicting intuitions about biological complexity, while taking into account several distinctions in the usage of the concept that are often overlooked. In particular, I propose a (...) distinction between two kinds of complexity, “mechanical” and “emergent”, which can be understood as different ways of relating the effective complexity of mechanisms and of behaviors in biological explanations. I illustrate the adequacy of this framework by discussing different attempts to understand intracellular organization in terms of pathways and networks. My framework provides a different way of thinking about recent philosophical debates, for example, on the difference between mechanistic and topological explanations and about the concept of emergence. Moreover, it can contribute to a proper assessment of metascientific arguments that invoke biological complexity. (shrink)

Developmental systems theory (DST) expands the unit of replication from genes to whole systems of developmental resources, which DST interprets in terms of cycling developmental processes. Expansion seems required by DST's argument against privileging genes in evolutionary and developmental explanations of organic traits. DST and the expanded replicator brook no distinction between biological and cultural evolution. However, by endorsing a single expanded unit of inheritance and leaving the classical molecular notion of gene intact, DST achieves only a nominal reunification of (...) heredity and development. I argue that an alternative conceptualization of inheritance denies the classical opposition of genetics and development while avoiding the singularity inherent in the replicator concept. It also yields a new unit--the reproducer--which genuinely integrates genetic and developmental perspectives. The reproducer concept articulates the non-separability of "genetic" and "developmental" roles in units of heredity, development, and evolution. DST reformulated in terms of reproducers rather than replicators preserves an empirically interesting distinction between cultural and biological evolution. (shrink)

The themes, problems and challenges of developmental systems theory as described in Cycles of Contingency are discussed. We argue in favor of a robust approach to philosophical and scientific problems of extended heredity and the integration of behavior, development, inheritance, and evolution. Problems with Sterelny's proposal to evaluate inheritance systems using his `Hoyle criteria' are discussed and critically evaluated. Additional support for a developmental systems perspective is sought in evolutionary studies of performance and behavior modulation of fitness.

In this paper we identify six theses that constitute core results of philosophical investigation into the nature of mechanisms, and of the role that the search for and identification of mechanisms play in the sciences. These theses represent the fruits of the body of research that is now often called New Mechanism. We concisely present the main arguments for these theses. In the literature, these arguments are scattered and often implicit. Our analysis can guide future research in many ways: it (...) provides critics of New Mechanism with clear targets, it can reduce misunderstandings, it can clarify differences of opinion among New Mechanists and it helps to define a research agenda for New Mechanists. (shrink)

Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

Philosophers of science increasingly believe that much of science is concerned with understanding the mechanisms responsible for the production of natural phenomena. An adequate understanding of scientific research requires an account of how scientists develop and test models of mechanisms. This paper offers a general account of the nature of mechanical models, discussing the representational relationship that holds between mechanisms and their models as well as the techniques that can be used to test and refine such models. The analysis is (...) supported by study of two competing models of a mechanism of speech perception. (shrink)

Summary The concept of unified theory is defined in logical and abstract semantic terms, and employed in the analysis of relations between empirical scientific theories. The conceptual framework of the approach applies to binary relations such as the reduction or replacement of one theory by another, and to multiple intertheory relations. Historically, unified theories tend to arise within the contexts of scientific conflicts which they may show susceptible of solution even in the most controversial cases of the logical incompatibility or (...) conceptual incommensurability of competing theories. These conclusions are exemplified by the Planck-Einstein quantum theory of thermal radiation. The analysis shows in which sense it can, and in which it cannot, be said that this theory unifies Wien's law and the Rayleigh-Jeans law of black-body radiation. (shrink)

Cognitive Science, Volume 46, Issue 8, August 2022.

I use Carl Gillett’s much heralded dimensioned theory of realization as a platform to develop a plausible part–whole theory. I begin with some basic desiderata for a theory of realization that its key terms should be defined and that it should be explanatory. I then argue that Gillett’s original theory violates these conditions because its explanatory force rests upon an unspecified “in virtue of” relation. I then examine Gillett’s later version that appeals instead to theoretical terms tied to “mechanisms.” Yet (...) I argue that it too violates the desiderata, since it defines realization for mechanisms in terms of two undefined ideas whose explanatory credentials have not been established—“implementation” and “grounds.” Thus I drop those ideas in favor of an explicit constraint that the parts and properties provide a mechanistic explanation. I also distinguish a special mechanistic theory from a preferred general theory that incorporates other kinds of part–whole explanations that target causal powers or capacities. The result is a theory that has the explanatory virtues of mechanistic theories as well as a broader scope desired by Gillett. I also compare the result to a similar idea from Robert Cummins that has been neglected in recent discussions of realization, namely, his general property analysis rather than his functional analysis. Finally, I defend the preferred general theory against possible objections that attempt to show a conflict between metaphysical demands on a theory of realization versus facts about good scientific explanation. (shrink)

A short review of complexity research from the perspective of history and philosophy of biology is presented. Complexity and its emergence has scientific and metaphysical meanings. From its beginning, biology was a science of complex systems, but with the advent of electronic computing and the possibility of simulating mathematical models of complicated systems, new intuitions of complexity emerged, together with attempts to devise quantitative measures of complexity. But can we quantify the complex?

The reductionist/holist debate seems an impoverished one, with many participants appearing to adopt a position first and constructing rationalisations second. Here I propose an intermediate position of pragmatic holism, that irrespective of whether all natural systems are theoretically reducible, for many systems it is completely impractical to attempt such a reduction, also that regardless if whether irreducible `wholes' exist, it is vain to try and prove this in absolute terms. This position thus illuminates the debate along new pragmatic lines, and (...) refocusses attention on the underlying heuristics of learning about the natural world. (shrink)

The reductionist/holist debate is highly polarised. I propose an intermediate position of pragmatic holism. It derives from two claims: firstly, that irrespective of whether all natural systems are theoretically reducible, for many systems it is utterly impractical to attempt such a reduction, and secondly, that regardless of whether irreducible 'wholes exist, it is vain to try and prove this. This position illuminates the debate along new pragmatic lines by refocussing attention on the underlying heuristics of learning about the natural world.

Philosophers have traditionally treated physicalism as an empirically informed metaphysical thesis. This approach faces a well-known problem often referred to as Hempel’s dilemma: formulations of physicalism tend to be either false or indeterminate. The generally preferred strategy to address this problem involves an appeal to a hypothetical complete and ideal physical theory. After demonstrating that this strategy is not viable, I argue that we should redefine physicalism as an interdisciplinary research program seeking to explain the mental in terms of the (...) physical that encompasses the physical sciences, the psychological and brain sciences, and philosophy. Redefining physicalism in this way improves upon previous reconstructive accounts while avoiding the indeterminacy associated with orthodox forms of futurist physicalism. (shrink)

The concept of levels of organization, despite its widespread scientific currency, has recently been criticized by a number of philosophers of science. This paper diagnoses the main source of problems facing theories of levels. On this basis, the problems with the usual criteria for distinguishing levels are evaluated: compositional relations, organizational types, and spatial scales. Drawing on some work on hierarchies in ecology, I argue in favor of an alternative conception of levels defined by the criterion of rates or time (...) scales of processes. (shrink)

Token physicalism is often viewed as a modest and unproblematic physicalist commitment, as contrasted with type physicalism. This paper argues that the prevalence of functional individuation in biology creates serious problems for token physicalism, because the latter requires that biological entities can be individuated physically and without reference to biological functioning. After characterizing the main philosophical roles for token physicalism, I describe the distinctive uses of functional individuation in models of biological processes. I then introduce some requirements on token identity (...) claims that arise from a position on individuation and identity known as sortalism. An examination of biological examples shows that these sortalist requirements cannot be plausibly met due to differences between individuation by functional biological criteria and by physical criteria. Even without assuming sortalism, token physicalism faces the more basic problem of excluding functionally irrelevant detail from the individuation of biological tokens. I close by suggesting that the philosophical roles for token identity are better fulfilled by a notion of token composition, which promotes a hierarchical picture of individuality. (shrink)

There have been repeated attempts in the history of comparative biology to provide a mechanistic account of morphological homology. However, it is well-established that homologues can develop from diverse sets of developmental causes, appearing not to share any core causal architecture that underwrites character identity. We address this challenge with a new conceptual model of Character Identity Mechanisms. ChIMs are cohesive mechanisms with a recognizable causal profile that allows them to be traced through evolution as homologues despite having a diverse (...) etiological organization. Our model hypothesizes that anatomical units at different levels of organization—cell types, tissues, and organs—have level-specific ChIMs with different conserved parts, activities, and organization. Relying on a methodology of conceptual engineering, we show how the ChIM concept advances our understanding of the developmental basis of morphological characters, while forging an important link between comparative and mechanistic biology. (shrink)

Convincing disputes about explanatory reductionism in the philosophy of biology require a clear and precise understanding of what a reductive explanation in biology is. The central aim of this book is to provide such an account by revealing the features that determine the reductive character of a biological explanation. Chapters I-IV provide the ground, on which I can then, in Chapter V, develop my own account of explanatory reduction in biology: Chapter I reveals the meta-philosophical assumptions that underlie my analysis (...) of reduction, Chapter II introduces the previous debate about reduction in the philosophy of biology by pointing out the most crucial lessons one should learn from this debate, Chapter III critically discusses the two perspectives on explanatory reduction that have been proposed in the philosophy of biology so far, and Chapter IV clarifies in what ways the issue of reduction is entangled with the issue of explanation. In Chapter V I present my own account of explanatory reduction. My main claim is that reductive explanations in the biological sciences possess three main characteristics: they explain the behavior of a biological system S, first, exclusively in terms of factors that are located on a lower level of organization than S, second, by focusing on factors that are internal to S , and third, by describing the genuine parts of S only as “parts in isolation”. This account is ontic because it traces the reductivity of an explanation back to certain relations that exist in the world. (shrink)

A long-standing problem in understanding goal-directed systems has been the insufficiency of mechanistic explanations to make sense of them. This paper offers a solution to this problem. It begins by observing the limitations of mechanistic decompositions when it comes to understanding physical fields. We argue that introducing the field concept, as it has been developed in field theory, alongside mechanisms is able to provide an account of goal directedness in the sciences.

This paper argues that the account of teleology previously proposed by the authors is consistent with the physical determinism that is implicit across many of the sciences. We suggest that much of the current aversion to teleological thinking found in the sciences is rooted in debates that can be traced back to ancient natural science, which pitted mechanistic and deterministic theories against teleological ones. These debates saw a deterministic world as one where freedom and agency is impossible. And, because teleological (...) entities seem to be free to either reach their ends or not, it was assumed that they could not be deterministic. Mayr’s modern account of teleonomy adheres to this basic assumption. Yet, the seeming tension between teleology and determinism is illusory because freedom and agency do not, in fact, conflict with a deterministic world. To show this, we present a taxonomy of different types of freedom that we see as inherent in teleological systems. Then we show that our taxonomy of freedom, which is crucial to understanding teleology, shares many of the features of a philosophical position regarding free will that is known in the contemporary literature as ‘compatibilism’. This position maintains that an agent is free when the sources of its actions are internal, when the agent itself is the deterministic cause of those actions. Our view shows that freedom is not only indispensable to teleology, but also that, contrary to common intuitions, there is no conflict between teleology and causal determinism. (shrink)

The current view of the relationship between areas of the mind-brain sciences is one where cross-disciplinary collaboration is required to advance claims about the mind-brain that stand on firm epistemic footing. My goal in this dissertation is to analyze what it means for information from different areas of science to fit together to produce strong epistemic claims by addressing how and to what extent claims about the mind-brain are corroborated in scientific practice. Philosophers of science have advanced various concepts of (...) the notion of fitting together information from different areas of science and its relation to scientific progress (e.g., Bickle, 1998, 2003, 2006; Darden and Maull, 1977; Mitchell, 2002, 2003; Mitchell and Dietrich, 2006; Nagel 1949, 1970, 1979; Piccinini and Craver, 2011; and Roskies, 2010). However, each concept of fitting together is vague and subject to multiple clarificatory questions. To get a handle on the notion of fitting together, I introduce the term ‘interdisciplinary corroboration’ as a placeholder for the various accounts of fitting together to facilitate my investigation of how claims about the mind-brain are corroborated in scientific practice. I argue review papers are a good place to begin analyzing interdisciplinary corroboration; accordingly, I conduct a two-part analysis of a review paper by Eichenbaum (2013) entitled ‘Memory on Time’. I use the lessons from my analysis to develop and advance a methodology for philosophers of science interested in knowledge production for evaluating review papers for corroboration in the mind-brain sciences. (shrink)

We highlight the limitations of formal methods by exhibiting two results in recursive function theory: that there is no effective means of finding a program that satisfies a given formal specification; or checking that a program meets a specification. We also exhibit a ‘simple’ MAS which has all the power of a Turing machine. We then argue that any ‘pure design’ methodology will face insurmountable difficulties in today’s open and complex MAS. Rather we suggest a methodology based on the classic (...) experimental method – that is ‘scientific foundations’ for the construction and control of complex MAS. (shrink)

When modelling complex systems one can not include all the causal factors, but one has to settle for partial models. This is alright if the factors left out are either so constant that they can be ignored or one is able to recognise the circumstances when they will be such that the partial model applies. The transference of knowledge from the point of application to the point of learning utilises a combination of recognition and inference ­ a simple model of (...) the important features is learnt and later situations where inferences can be drawn from the model are recognised. Context is an abstraction of the collection of background features that are later recognised. Different heuristics for recognition and model formulation will be effective for different learning tasks. Each of these will lead to a different type of context. Given this, there are (at least) two ways of modelling context: one can either attempt to investigate the contexts that arise out of the heuristics that a particular agent actually applies (the `internal' approach); or (if this is feasible) one can attempt to model context using the external source of regularity that the heuristics exploit. There are also two basic methodologies for the investigation of context: a top-down (or `foundationalist') approach where one tries to lay down general, a priori principles and a bottom-up (or `scientific') approach where one can try and find what sorts of context arise by experiment and simulation. A simulation is exhibited which is designed to illustrate the practicality of the bottom-up approach in elucidating the sorts of internal context that arise in an artificial agent which is attempting to learn simple models of a complex environment. It ends with a plea for the cooperation of the AI and Machine Learning communities as both learning and inference is needed if context is to make complete sense. (shrink)

Although the role of morphology in evolutionary theory remains a subject of debate, assessing the contributions of morphological investigation to evolutionary developmental biology (Evo-devo) is a more circumscribed issue of direct relevance to ongoing research. Historical studies of morphologically oriented researchers and the formation of the Modern Synthesis in the Anglo-American context identify a recurring theme: the synthetic theory of evolution did not capture multiple levels of biological organization. When this feature is incorporated into a philosophical framework for explaining the (...) origin of evolutionary innovations and novelties (a core domain of inquiry in Evo-devo) two specific roles for morphology can be described: (1) the conceptualization and operational identification of the targets of explanation; and (2) the elucidation of causal interactions at higher levels of organization during ontogeny and through evolutionary time. These roles are critical components of any adequate explanation of innovation and novelty though not exhaustive of the parts played by morphology in evolutionary investigation. They also invite reflection on what counts as an evolutionary cause in contemporary evolutionary biology. (shrink)