A real‐world rational agent: unifying old and new AI

Explanations of cognitive processes provided by traditional artificial intelligence were based on the notion of the knowledge level. This perspective has been challenged by new AI that proposes an approach based on embodied systems that interact with the real‐world. We demonstrate that these two views can be unified. Our argument is based on the assumption that knowledge level explanations can be defined in the context of Bayesian theory while the goals of new AI are captured by using a well established robot based model of learning and problem solving, called Distributed Adaptive Control (DAC). In our analysis we consider random foraging and we prove that minor modifications of the DAC architecture renders a model that is equivalent to a Bayesian analysis of this task. Subsequently, we compare this enhanced, “rational,” model to its “non‐rational” predecessor and a further control condition using both simulated and real robots, in a variety of environments. Our results show that the changes made to the DAC architecture, in order to unify the perspectives of old and new AI, also lead to a significant improvement in random foraging.     

A note on schema and exemplar approaches to motor skill representation in memory

Given the need for a memory representation of well-learned motor skills, a common assumption in motor behavior is that this knowledge is stored in a central, abstracted form. Active production of motor skills has not been used in experimental designs that have provided empirical support for this view of representation, however. Much of the faith in centralized, abstracted forms of memory representation for motor skills is due to the popularity of Schmidt's schema theory, which has adapted the prototype abstraction model from category learning research to the representation of motor skills. Since schema theory was proposed, however, an alternative view that seriously questions the preeminence of the prototype abstraction model for the central representation of knowledge has arisen in the category learning literature. This particular view, termed the specific exemplar model, has led a number of researchers in cognition to develop mixed models that involve both prototypic abstraction and specific exemplar elements. This note, then, identifies what can be perceived as a gap in the empirical knowledge base in motor behavior and discusses the possibility of using the debate about representation for category learning as a stimulus for initiating a similar investigation into the representation of motor skills. A hypothetical specific exemplar model for the memory representation of motor skills is outlined, and possible empirical comparisons between this model and the schema abstraction model are suggested.     

A Note on Schema and Exemplar Approaches to Motor Skill Representation in Memory

Given the need for a memory representation of well-learned motor skills, a common assumption in motor behavior is that this knowledge is stored in a central, abstracted form. Active production of motor skills has not been used in experimental designs that have provided empirical support for this view of representation, however. Much of the faith in centralized, abstracted forms of memory representation for motor skills is due to the popularity of Schmidt's schema theory, which has adapted the prototype abstraction model from category learning research to the representation of motor skills. Since schema theory was proposed, however, an alternative view that seriously questions the preeminence of the prototype abstraction model for the central representation of knowledge has arisen in the category learning literature. This particular view, termed the specific exemplar model, has led a number of researchers in cognition to develop mixed models that involve both prototypic abstraction and specific exemplar elements. This note, then, identifies what can be perceived as a gap in the empirical knowledge base in motor behavior and discusses the possibility of using the debate about representation for category learning as a stimulus for initiating a similar investigation into the representation of motor skills. A hypothetical specific exemplar model for the memory representation of motor skills is outlined, and possible empirical comparisons between this model and the schema abstraction model are suggested.     

Combining Prototypes: A Selective Modification Model

We propose a model that accounts for how people construct prototypes for composite concepts out of prototypes for simple concepts. The first component of the model is a prototype representation for simple, noun concepts, such as fruit, which specifies: (1) the relevant attributes of the concepts, (2) the possible values of each attribute, (3) the salience of each value, and (4) the diagnosticity of each attribute. The second component of the model specifies procedures for modifying simple prototypes so that they represent new, composite concepts. The procedure for adjectival modification, as when red modifies fruit, consists of selecting the relevant attribute(s) in the noun concept (color), boosting the diagnosticity of that attribute, and increasing the salience of the value named by the adjective (red). The procedure for adverbial modification, as in very red fruit, consists of multiplication-by-o-scalar of the salience of the relevant value (red). The outcome of these procedures is a new prototype representation. The third component of the model is tversky's (1977) contrast rule for determining the similarity between a representation for a prototype and one for an instance. The model is shown to be consistent with previous findings about prototypes in general, as well as with specific findings about typicality judgments for adjective-noun conjunctions. Four new experiments provide further detailed support for the model.     

Meta-Argumentation Modelling I: Methodology and Techniques

In this paper, we introduce the methodology and techniques of meta-argumentation to model argumentation. The methodology of meta-argumentation instantiates Dung’s abstract argumentation theory with an extended argumentation theory, and is thus based on a combination of the methodology of instantiating abstract arguments, and the methodology of extending Dung’s basic argumentation frameworks with other relations among abstract arguments. The technique of meta-argumentation applies Dung’s theory of abstract argumentation to itself, by instantiating Dung’s abstract arguments with meta-arguments using a technique called flattening. We characterize the domain of instantiation using a representation technique based on soundness and completeness. Finally, we distinguish among various instantiations using the technique of specification languages.     

Fuzzy rough sets: Survey and proposal of an enhanced knowledge representation model based on automatic noisy sample detection

Fuzzy Rough Set (FRS) theory, which has been emerged thanks to unifying Rough Set and Fuzzy Set ones, is a powerful mathematical tool for handling and processing real data of imprecise, incomplete, inconsistent and uncertain nature. It has drawn attention of many researchers, scientists and industrials in various domains over the last three decades. However, different studies have showed that its classical knowledge representation model has a main weakness linked to its sensitivity to data noise which decreases both its effectiveness and application scope. In this paper, we survey the current FRS paradigms developed to deal with this issue and propose a new FRS model based on the Automatic Noisy Sample Detection (ANSD-FRS) able to cope with noise influence in classification tasks. Besides, we study the principal properties of this new model and reformulate the most applied FRS concepts relying on its operators. Numerous experiments have been conducted to analyze the ANSD-FRS behavior compared to the commonly used FRS models reputed as the most noise-resistant paradigms. These experiment results have proved the performance and robustness of the ANSD-FRS in comparison with those renowned models.     

Language and connectionism: the developing interface

After a difficult initial period in which connectionism was perceived as either irrelevant or antithetical to linguistic theory, connectionist concepts are now beginning to be brought to bear on basic issues concerning the structure, acquisition, and processing of language, both normal and disordered. This article describes some potential points of further contact between connectionism and linguistic theory. I consider how connectionist concepts may be relevant to issues concerning the representation of linguistic knowledge; the role of a priori constraints on acquisition; and the poverty of the stimulus argument. I then discuss whether these models contribute to the development of explanatory theories of language.     

Inductive Reasoning in Alzheimer''s Disease

We evaluated knowledge of basic level and superordinate semantic relations and the role of cognitive resources during inductive reasoning in probable Alzheimer's disease (AD). Nineteen mildly demented AD patients and 17 healthy control subjects judged the truthfulness of arguments with a premise and a conclusion that contain familiar concepts coupled with "blank" predicates, such as "Spiders contain phosphatidylcholine; therefore all insects contain phosphatidylcholine." Like healthy control subjects, AD patients were relatively insensitive to the typicality of the premise category when judging the strength of arguments with a conclusion containing a basic-level concept, but were relatively sensitive to typicality during judgments of arguments containing a superordinate in the conclusion. Moreover, AD patients resembled control subjects in judging arguments with an immediate superordinate in the conclusion compared to arguments with a distant superordinate. AD patients differed from control subjects because they could not take advantage of two premises in an argument containing basic-level concepts. We conclude that semantic knowledge is sufficiently preserved in AD to support inductive reasoning, but that limited cognitive resources may interfere with AD patients' ability to consider the entire spectrum of information available during semantic challenges.     

人造物概念的表征：功能、意图和目的论的解释

以概念结构研究从“相似”到“解释”的理论转向为背景,评述人造物领域的“意图-历史论”（Bloom, 1996）,提出人造物概念结构中自上而下的约束是来自“使用目的”而不是“设计意图”。分析近期报告的大量实验,最后提出人造物概念表征的“基于使用的目的论”的解释模式和人造物归类的双重目标模型。     

What New Wave Materialists Can't Say

Most phenomenal concept strategists, or concept dualists, trace the explanatory gap to “thin” phenomenal concepts that fail to represent phenomenal properties as physical entities. New Wave Materialists, a subgroup of concept dualists, claim that our physical and phenomenal concepts each represent experience completely and accurately, but nevertheless so differently that a priori links don't (and can't) hold between them. This paper argues that you can't have two distinct but nevertheless complete and accurate representations of the same thing. One (or both) of the representations must misrepresent, or the two representations must represent different things. The paper then puts its arguments in a wider context. It notes that our phenomenal concepts must be transparent, translucent, mildly opaque, or radically opaque (in senses reviewed in the paper). It canvasses arguments that a posteriori physicalists can't consider our phenomenal concepts opaque. Then it shows how its own arguments against New Wave Materialism have the result that a posteriori physicalists can't consider phenomenal concepts transparent or translucent. The paper thus advances its arguments as part of a broad‐based case against a posteriori physicalism.     

The epistemic significance of valid inference

The traditional picture of logic takes it for granted that ??valid arguments have a fundamental epistemic significance??, but neither model theory nor traditional proof theory dealing with formal system has been able to give an account of this significance. Since valid arguments as usually understood do not in general have any epistemic significance, the problem is to explain how and why we can nevertheless use them sometimes to acquire knowledge. It is suggested that we should distinguish between arguments and acts of inferences and that we have to reconsider the latter notion to arrive at the desired explanation. More precisely, the notions should be developed so that the following relationship holds: one gets in possession of a ground for a conclusion by inferring it from premisses for which one already has grounds, provided that the inference in question is valid. The paper proposes explications of the concepts of ground and deductively valid inference so that this relationship holds as a conceptual truth. Logical validity of inference is seen as a special case of deductive validity, but does not add anything as far as epistemic significance is concerned??it resides already in the deductively valid inferences.     

What Assertion Doesn't Show

Abstract: Some recent arguments against the classical invariantist account of knowledge exploit the idea that there is a ‘knowledge norm’ for assertion. It is claimed that, given the existence of this norm, certain intuitions about assertability support contextualism, or contrastivism, over classical invariantism. In this paper I show that, even if we accept the existence of a knowledge norm, these assertability‐based arguments fail. The classical invariantist can accommodate and explain the relevant intuitions about assertability, in a way that retains the idea that knowledge is the epistemic norm for assertion. When we consider the role of assertion as a conversational act, it becomes plausible that a subject's epistemic warrant to assert can be defeated even though she has knowledge. This defeasibility thesis is what allows the classical invariantist to accommodate and explain the kinds of intuitions on which assertability‐based arguments depend.     

Exemplars and prototypes in natural language concepts: A typicality-based evaluation

Are natural language categories represented by instances of the category or by a summary representation? We used an exemplar model and a prototype model, both derived within the framework of the generalized context model (Nosofsky, 1984, 1986), to predict typicality ratings for 12 superordinate natural language concepts. The models were fitted to typicality ratings averaged across participants and to the typicality judgments of individual participants. Both analyses yielded results in favor of the exemplar model. These results suggest that higher-level natural language concepts are represented by their subordinate members, rather than by a summary representation.     

The representation of abstract words: why emotion matters

Although much is known about the representation and processing of concrete concepts, knowledge of what abstract semantics might be is severely limited. In this article we first address the adequacy of the 2 dominant accounts (dual coding theory and the context availability model) put forward in order to explain representation and processing differences between concrete and abstract words. We find that neither proposal can account for experimental findings and that this is, at least partly, because abstract words are considered to be unrelated to experiential information in both of these accounts. We then address a particular type of experiential information, emotional content, and demonstrate that it plays a crucial role in the processing and representation of abstract concepts: Statistically, abstract words are more emotionally valenced than are concrete words, and this accounts for a residual latency advantage for abstract words, when variables such as imageability (a construct derived from dual coding theory) and rated context availability are held constant. We conclude with a discussion of our novel hypothesis for embodied abstract semantics.     

Cognitive Architecture, Concepts, and Introspection: An Information‐Theoretic Solution to the Problem of Phenomenal Consciousness

This essay is a sustained attempt to bring new light to some of the perennial problems in philosophy of mind surrounding phenomenal consciousness and introspection through developing an account of sensory and phenomenal concepts. Building on the information‐theoretic framework of Dretske (1981) , we present an informational psychosemantics as it applies to what we call sensory concepts, concepts that apply, roughly, to so‐called secondary qualities of objects. We show that these concepts have a special informational character and semantic structure that closely tie them to the brain states realizing conscious qualitative experiences. We then develop an account of introspection which exploits this special nature of sensory concepts. The result is a new class of concepts, which, following recent terminology, we call phenomenal concepts: these concepts refer to phenomenal experience itself and are the vehicles used in introspection. On our account, the connection between sensory and phenomenal concepts is very tight: it consists in different semantic uses of the same cognitive structures underlying the sensory concepts, such as the concept of red. Contrary to widespread opinion, we show that information theory contains all the resources to satisfy internalist intuitions about phenomenal consciousness, while not offending externalist ones. A consequence of this account is that it explains and predicts the so‐called conceivability arguments against physicalism on the basis of the special nature of sensory and phenomenal concepts. Thus we not only show why physicalism is not threatened by such arguments, but also demonstrate its strength in virtue of its ability to predict and explain away such arguments in a principled way. However, we take the main contribution of this work to be what it provides in addition to a response to those conceivability arguments, namely, a substantive account of the interface between sensory and conceptual systems and the mechanisms of introspection as based on the special nature of the information flow between them.     

Gender/Body/Machine

This article considers the question of embodiment in relation to gender and whether there are models of artificial intelligence (AI) which can enrol a concept of gender in their design. A central concern for feminist epistemology is the role of the body in the making of knowledge. I consider how this may inform a critique of the AI project and the related area of artificial life (A–Life), the latter area being of most interest in this paper. I explore briefly the tensions between the treatment of the body in different branches of feminist theory, especially the tensions between the approaches of feminist sociology and feminist philosophy. I explore the ways in which writing from category theory and anthropological phenomenology offers rich suggestions as to how the body has been left out of objectivist accounts of epistemology, but struggles to offer an account of why . In its analysis of the links between women, knowledge and the body, feminist revisions of epistemology offer a more convincing why . This is explored briefly through a critique of symbolic AI, and more substantially through the problem of embodiment in artificial life.     

Automatically deriving readers’ knowledge structures from texts

Latent semantic analysis (LSA) serves as both a theory and a method for representing the meaning of words based on a statistical analysis of their contextual usage (Foltz, 1996; Landauer & Dumais, 1997). In experiments in the domains of psychology and history, we compared the representation of readers’ knowledge structures of information learned from texts with the representation generated by LSA. Results indicated that LSA’s representation is similar to readers’ representations. In addition, the degree to which the reader’s representation is similar to LSA’s representation is indicative of the amount of knowledge the reader has acquired and of the reader’s reading ability. This approach has implications both as a model of learning from text and as a practical tool for performing knowledge assessment.     

General-purpose content

In this paper, I consider the objection, raised by Radu Bogdan, that a teleological theory of content is unable to ascribe content to a general-purpose, doxastic system. I begin by giving some attention to the notion of general-purpose representation, and suggest that this notion can best be understood as what I term "interest-independent" representation. I then outline Bogdan's objection in what I take to be its simplest form. I attempt to counter the objection by explaining how a teleologist might ascribe content in a particular case - the case of a perceptual judgement whose content is learned. I reject the idea that the teleologist can appeal to the way in which the subject has used the judgement, or its constituent concepts, in the past, on the grounds that it is possible for the subject to produce judgements and concepts that never help her to satisfy any of her interests. Instead, my account depends on the idea that the process of learning is regulated by a mechanism whose function is to produce a harmony between the information carried by perceptual judgements and the way in which they are used in inference.