Misunderstandings often develop when scientists from different backgrounds use the same words (e.g., “selection”) when they mean different things by them. Theorists must therefore choose and define their terms carefully. In addition, proponents of “new” theories need to demonstrate empirically that theirs are more powerful than the existing theories they wish to supplant. Wilson & Sober have not yet done this.

The six commentaries raise five issues about multi-level selection theory that we attempt to address: (1) replicators without vehicles, (2) group selection and movement between groups, (3) absolute versus relative fitness, (4) group-level psychological adaptions, and (5) multi-level selection as a predictive theory.

This volume is a collection of some of the most important philosophical papers by Peter Gärdenfors. Spanning a period of more than 20 years of his research, they cover a wide ground of topics, from early works on decision theory, belief revision and nonmonotonic logic to more recent work on conceptual spaces, inductive reasoning, semantics and the evolutions of thinking. Many of the papers have only been published in places that are difficult to access. The common theme of all the (...) papers is the dynamics of thought. Several of the papers have become minor classics and the volume bears witness of the wide scope of Gärdenfors’ research and of his crisp and often witty style of writing. The volume will be of interest to researchers in philosophy and other cognitive sciences. (shrink)

Now in so far as it is recognized that the constituents of the environment are not present inside the body in the same way as they are present outside it, to that extent they are bound, the moment they are inside it, to become something essentially different from the environment.

The six commentaries raise five issues about multi-level selection theory that we attempt to address: (1) replicators without vehicles, (2) group selection and movement between groups, (3) absolute versus relative fitness, (4) group-level psychological adaptions, and (5) multi-level selection as a predictive theory.

How many words—and which ones—are sufficient to define all other words? When dictionaries are analyzed as directed graphs with links from defining words to defined words, they reveal a latent structure. Recursively removing all words that are reachable by definition but that do not define any further words reduces the dictionary to a Kernel of about 10% of its size. This is still not the smallest number of words that can define all the rest. About 75% of the Kernel turns (...) out to be its Core, a “Strongly Connected Subset” of words with a definitional path to and from any pair of its words and no word's definition depending on a word outside the set. But the Core cannot define all the rest of the dictionary. The 25% of the Kernel surrounding the Core consists of small strongly connected subsets of words: the Satellites. The size of the smallest set of words that can define all the rest—the graph's “minimum feedback vertex set” or MinSet—is about 1% of the dictionary, about 15% of the Kernel, and part-Core/part-Satellite. But every dictionary has a huge number of MinSets. The Core words are learned earlier, more frequent, and less concrete than the Satellites, which are in turn learned earlier, more frequent, but more concrete than the rest of the Dictionary. In principle, only one MinSet's words would need to be grounded through the sensorimotor capacity to recognize and categorize their referents. In a dual-code sensorimotor/symbolic model of the mental lexicon, the symbolic code could do all the rest through recombinatory definition. (shrink)

Wilson & Sober's discussion of group selection is marred by the absence of plausible examples of human group-level behavioral adaptation. The trait of authoritarianism is one possible example of such an adaptation. It reduces within-group variance in reproductive success, manifests itself more strongly in response to group-level threat, and is found in a variety of cultures.

This article proposes a number of models to examine through which mechanisms a population of autonomous agents could arrive at a repertoire of perceptually grounded categories that is sufficiently shared to allow successful communication. The models are inspired by the main approaches to human categorisation being discussed in the literature: nativism, empiricism, and culturalism. Colour is taken as a case study. Although we take no stance on which position is to be accepted as final truth with respect to human categorisation (...) and naming, we do point to theoretical constraints that make each position more or less likely and we make clear suggestions on what the best engineering solution would be. Specifically, we argue that the collective choice of a shared repertoire must integrate multiple constraints, including constraints coming from communication. Key Words: autonomous agents; colour categorisation; colour naming; connectionism; cultural evolution; genetic evolution; memes; origins of language; self-organisation; semiotic dynamics; symbol grounding. (shrink)

The inductive category formation framework, an influential set of theories of learning in psychology and artificial intelligence, is deeply flawed. In this framework a set of necessary and sufficient features is taken to define a category. Such definitions are not functionally justified, are not used by people, and are not inducible by a learning system. Inductive theories depend on having access to all and only relevant features, which is not only impossible but begs a key question in learning. The crucial (...) roles of other cognitive processes (such as explanation and credit assignment) are ignored or oversimplified. Learning necessarily involves pragmatic considerations that can only be handled by complex cognitive processes.We provide an alternative framework for learning according to which category definitions must be based on category function. The learning system invokes other cognitive processes to accomplish difficult tasks, makes inferences, analyses and decides among potential features, and specifies how and when categories are to be generated and modified. We also examine the methodological underpinnings of the two approaches and compare their motivations. (shrink)

According to one productive and influential approach to cognition, categorization, object recognition, and higher level cognitive processes operate on a set of fixed features, which are the output of lower level perceptual processes. In many situations, however, it is the higher level cognitive process being executed that influences the lower level features that are created. Rather than viewing the repertoire of features as being fixed by low-level processes, we present a theory in which people create features to subserve the representation (...) and categorization of objects. Two types of category learning should be distinguished. Fixed space category learning occurs when new categorizations are representable with the available feature set. Flexible space category learning occurs when new categorizations cannot be represented with the features available. Whether fixed or flexible, learning depends on the featural contrasts and similarities between the new category to be represented and the individual's existing concepts. Fixed feature approaches face one of two problems with tasks that call for new features: If the fixed features are fairly high level and directly useful for categorization, then they will not be flexible enough to represent all objects that might be relevant for a new task. If the fixed features are small, subsymbolic fragments (such as pixels), then regularities at the level of the functional features required to accomplish categorizations will not be captured by these primitives. We present evidence of flexible perceptual changes arising from category learning and theoretical arguments for the importance of this flexibility. We describe conditions that promote feature creation and argue against interpreting them in terms of fixed features. Finally, we discuss the implications of functional features for object categorization, conceptual development, chunking, constructive induction, and formal models of dimensionality reduction. Key Words: concept learning; conceptual development; features; perceptual learning; stimulus encoding. (shrink)

We address the problem of predicting how people will spontaneously divide into groups a set of novel items. This is a process akin to perceptual organization. We therefore employ the simplicity principle from perceptual organization to propose a simplicity model of unconstrained spontaneous grouping. The simplicity model predicts that people would prefer the categories for a set of novel items that provide the simplest encoding of these items. Classification predictions are derived from the model without information either about the number (...) of categories sought or information about the distributional properties of the objects to be classified. These features of the simplicity model distinguish it from other models in unsupervised categorization (where, for example, the number of categories sought is determined via a free parameter), and we discuss how these computational differences are related to differences in modeling objectives. The predictions of the simplicity model are validated in four experiments. We also discuss the significance of simplicity in cognitive modeling more generally. (shrink)

Humans appear to be possible candidates for group selection because they are often said to live in bands, clans, and tribes. These terms, however, are only names for conceptual categories of people. They do not designate enduring bounded gatherings of people that might be “vehicles of selection.” Hence, group selection has probably not been a major force in human evolution.

Many current neurophysiological, psychophysical, and psychological approaches to vision rest on the idea that when we see, the brain produces an internal representation of the world. The activation of this internal representation is assumed to give rise to the experience of seeing. The problem with this kind of approach is that it leaves unexplained how the existence of such a detailed internal representation might produce visual consciousness. An alternative proposal is made here. We propose that seeing is a way of (...) acting. It is a particular way of exploring the environment. Activity in internal representations does not generate the experience of seeing. The out- side world serves as its own, external, representation. The experience of seeing occurs when the organism masters what we call the gov- erning laws of sensorimotor contingency. The advantage of this approach is that it provides a natural and principled way of accounting for visual consciousness, and for the differences in the perceived quality of sensory experience in the different sensory modalities. Sev- eral lines of empirical evidence are brought forward in support of the theory, in particular: evidence from experiments in sensorimotor adaptation, visual “filling in,” visual stability despite eye movements, change blindness, sensory substitution, and color perception. (shrink)

I argue that a concept is applied correctly when it is applied to the kind of things it is the concept of. Correctness as successful kind-tracking is fulfilling an externally and naturalistically individuated standard. And the normative aspect of concept-application so characterized depends on the relational (non-individualistic) feature of conceptual content. I defend this view against two objections. The first is that norms should provide justifications for action, and the second involves a version of the thesis of indeterminacy of reference.

An action-oriented theory of embodied memory is favorable for many reasons, but it will not provide a quick yet clean solution to the grounding problem in the way Glenberg (1997t) envisages. Although structural mapping via analogical representations may be an adequate mechanism of cognitive representation, it will not suffice to explain representation as such.

Group selection may be defined either broadly or narrowly. Narrowly defined group selection may involve either selection for altruism or group selection between alternative evolutionarily stable states. The last variety of group selection is likely to have been particularly important in human evolution.

Steels & Belpaeme's (S&B's) simulations contain all the right components, but they are put together wrongly. Color categories are unrepresentative of categories in general and language is not merely naming. Language evolved because it provided a powerful new way to acquire categories (through instruction, rather than just the old way of other species, through trial-and-error experience). It did not evolve so that multiple agents looking at the same objects could let one another know which of the objects they had in (...) mind, co-coining names for them on the fly. (shrink)

In approaching the question of whether groups of people can have cognitive capacities that are fundamentally different than the cognitive capacities of the individuals within the group, we lay out a Multiple, Interactive Levels of Cognitive Systems (MILCS) framework. The goal of MILCS is to explain the kinds of cognitive processes typically studied by cognitive scientists, such as perception, attention, memory, categorization, decision making, problem solving, and judgment. Rather than focusing on high-level constructs such as modules in an information processing (...) flow diagram or internal representations, MILCS focuses on mechanisms that allow systems to engage in flexible, adaptive behavior. Examples of these mechanisms are network structure-process pairs that: combine data from perception with top-down theories, achieve consistency and consensus through information exchange, selectively attend to information globally assessed as relevant, and develop specialized units from originally homogeneous networks through competition among the units. Two such systems are considered in some detail -- lateral inhibition within a network for selecting from a candidate set the option that is most attractive, and a diffusion process for accumulating evidence to reach a generally rapid and accurate decision. These system descriptions are aptly applied at multiple levels, including within and across people. These systems provide accounts that unify cognitive processes across multiple levels, can be expressed in a common vocabulary provided by network science, are inductively powerful yet appropriately constrained, and are applicable to a large number of superficially diverse cognitive systems. Given that people are typically highly motivated to participate in strong groups, cognitively resourceful people will tend to form groups that effectively employ cognitive systems at higher levels than the individuals. The impressive cognitive capacities of individual people do not eliminate the need to talk about group cognition. Instead, smart people generally form smart groups. (shrink)

Categorical perception (CP) refers to how similar things look different depending on whether they are classified as the same category. Many studies demonstrate that adult humans show CP for human emotional faces. It is widely debated whether the effect can be accounted for solely by perceptual differences (structural differences among emotional faces) or whether additional perceiver-based conceptual knowledge is required. In this review, I discuss the phenomenon of CP and key studies showing CP for emotional faces. I then discuss a (...) new model of emotion which highlights how perceptual and conceptual knowledge interact to explain how people see discrete emotions in others’ faces. In doing so, I discuss how language (emotion words included in the paradigm) contribute to CP. (shrink)

This article presents a detailed formal approach to concepts and concept combination. Sense generation is a competence‐level theory that attempts to respect constraints from the various cognitive sciences, and postulates “quasi‐classical” conceptual structures where attributes receive only one value (but are defeasible and so do not represent necessary and sufficient conditions on category membership) and where classification is binary (but explicitly context‐sensitive). It is also argued that any general theory of concepts must account for “privative” combinations (e.g., stone lion, fake (...) gun, apparent friend) as extreme test‐cases of representational and classificatory flexibility. The approach presented therefore provides a treatment of these combinations. The approach differentiates between the “lexical concept” (the stable information represented in a mental lexicon) which acts as a base from which the various “senses” (flexible contents associated with words and phrases in context, and used in classification) are “generated.” Generation allows nonmonotonicity, so that in different circumstances, different attributes may be defeated or modified. Classification is treated as relative to the perspective adopted, so that a classification acceptable from one perspective may be unacceptable from another, without contradiction. The result is a view that assumes bottom‐up priority in concept combination, where the range of senses generated by bottom‐up rules of combination is tempered by pragmatic‐communicative constraints on classification. An account of the representational and classification behavior of privative combinations is outlined, and the article concludes with a discussion of some of the implications of the approach. (shrink)

Goldstein reported multiple cases of failure to categorise colours in patients that he termed amnesic or anomic aphasics. These patients have a particular difficulty in producing perceptual categories in the absence of other aphasic impairments. We hold that neuropsychological evidence supports the view that the task of colour categorisation is logically impossible without labels.

Colour vision plays a foundational explanatory role in the philosophy of colour, and serves as perennial quarry in the wider philosophy of perception. I present two contributions to our understanding of this notion. The first is to develop a constitutive approach to characterizing colour vision. This approach seeks to comprehend the nature of colour vision qua psychological kind, as contrasted with traditional experiential approaches, which prioritize descriptions of our ordinary visual experience of colour. The second contribution is to argue that (...) colour vision does not constitutively involve the ability to see colours, in a natural and categorically committed sense. I argue that two subjects exactly alike in respect of their constitutive colour vision abilities could differ in respect of whether or not they have categorical perception of colour. The argument is supported by thought experiment and dissociations observed in cognitive neuropsychology. The argument also bears connections to recent neo-Whorfian accounts of colour categorization. _1._ Introduction _2._ Colour Vision, Experience, and Natures _3._ The Central Argument _3.1._ Colour constancy and discrimination _3.2._ Dissociating colour vision and categorical perception for colour _4._ Whorf and the View from Cognitive Neuropsychology _5._ Conclusion. (shrink)

This article considers categorical perception (CP) as a crucial process involved in all sort of communication throughout the biological hierarchy, i.e. in all of biosemiosis. Until now, there has been consideration of CP exclusively within the functional cycle of perception–cognition–action and it has not been considered the possibility to extend this kind of phenomena to the mere physiological level. To generalise the notion of CP in this sense, I have proposed to distinguish between categorical perception (CP) and categorical sensing (CS) (...) in order to extend the CP framework to all communication processes in living systems, including intracellular, intercellular, metabolic, physiological, cognitive and ecological levels. The main idea is to provide an account that considers the heterarchical embeddedness of many instances of CP and CS. This will take me to relate the hierarchical nature of categorical sensing and perception with the equally hierarchical issues of the “binding problem”, “triadic causality”, the “emergent interpretant” and the increasing semiotic freedom observed in biological and cognitive systems. (shrink)

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...) brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components – not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored. (shrink)

Various defenses of amodal symbol systems are addressed, including amodal symbols in sensory-motor areas, the causal theory of concepts, supramodal concepts, latent semantic analysis, and abstracted amodal symbols. Various aspects of perceptual symbol systems are clarified and developed, including perception, features, simulators, category structure, frames, analogy, introspection, situated action, and development. Particular attention is given to abstract concepts, language, and computational mechanisms.