Commentators expressed a wide variety of views on whether there is a basic capacity limit of 3 to 5 chunks and, among those who believe in it, about why it occurs. In this response, I conclude that the capacity limit is real and that the concept is strengthened by additional evidence offered by a number of commentators. I consider various arguments why the limit occurs and try to organize these arguments into a conceptual framework or “metatheory” of storage capacity (...) limits meant to be useful in future research to settle the issue. I suggest that principles of memory representation determine what parts of the representation will be most prominent but that limits of attention (or of a memory store that includes only items that have been most recently attended) determine the 3- to 5-chunk capacity limit. (shrink)

The notion of a "mental representation" is, arguably, in the first instance a theoretical construct of cognitive science. As such, it is a basic concept of the Computational Theory of Mind, according to which cognitive states and processes are constituted by the occurrence, transformation and storage (in the mind/brain) of information-bearing structures (representations) of one kind or another.

Implicit and explicit attitudes manifest themselves as distinct and partly dissociable behavioral dispositions. It is natural to think that these differences reflect differing underlying representations. The present article argues that this may be a mistake. Although non-verbal and verbal measures of attitudes often dissociate, this may be because the two types of outcome-measure are differentially impacted by other factors, not because they are tapping into distinct kinds of representation or distinct storage systems. I arrive at this view through (...) closer consideration than is usual of the mechanisms and processes that underlie overt behavior. (shrink)

In attempting to integrate the authors' proposed model with results from analogous human event-related potential (ERP) research, we found difficulties with: (1) its apparent disregard for supraordinate representations at posterior multimodal association cortices, (2) its failure to address contextual task effects, and (3) its strict architectural dichotomy between memory storage and control functions.

The distinction between regular and irregular morphology is not clear-cut enough to suggest two distinct modular structures. Instead, regularity is tied directly to the type frequency of a pattern. Evidence from experiments as well as from naturally occurring sound change suggests that even regular forms have lexical storage. Finally, the development trajectory entailed by the dual-processing model is much more complex than that entailed by associative network models.

Natural language processing techniques contribute more and more in analyzing legal documents recently, which supports the implementation of laws and rules using computers. Previous approaches in representing a legal sentence often based on logical patterns that illustrate the relations between concepts in the sentence, often consist of multiple words. Those representations cause the lack of semantic information at the word level. In our work, we aim to tackle such shortcomings by representing legal texts in the form of abstract meaning (...) class='Hi'>representation, a graph-based semantic representation that gains lots of polarity in NLP community recently. We present our study in AMR Parsing and AMR-to-text Generation specifically for legal domain. We also introduce JCivilCode, a human-annotated legal AMR dataset which was created and verified by a group of linguistic and legal experts. We conduct an empirical evaluation of various approaches in parsing and generating AMR on our own dataset and show the current challenges. Based on our observation, we propose our domain adaptation method applying in the training phase and decoding phase of a neural AMR-to-text generation model. Our method improves the quality of text generated from AMR graph compared to the baseline model. 2018; and “Legal Text Generation fromMeaning Representation”, published in the 32nd International Conference on Legal Knowledge and Information Systems 2019.). (shrink)

Modeling law search and retrieval as prediction problems has recently emerged as a predominant approach in law intelligence. Focusing on the law article retrieval task, we present a deep learning framework named LamBERTa, which is designed for civil-law codes, and specifically trained on the Italian civil code. To our knowledge, this is the first study proposing an advanced approach to law article prediction for the Italian legal system based on a BERT (Bidirectional Encoder Representations from Transformers) learning framework, which has (...) recently attracted increased attention among deep learning approaches, showing outstanding effectiveness in several natural language processing and learning tasks. We define LamBERTa models by fine-tuning an Italian pre-trained BERT on the Italian civil code or its portions, for law article retrieval as a classification task. One key aspect of our LamBERTa framework is that we conceived it to address an extreme classification scenario, which is characterized by a high number of classes, the few-shot learning problem, and the lack of test query benchmarks for Italian legal prediction tasks. To solve such issues, we define different methods for the unsupervised labeling of the law articles, which can in principle be applied to any law article code system. We provide insights into the explainability and interpretability of our LamBERTa models, and we present an extensive experimental analysis over query sets of different type, for single-label as well as multi-label evaluation tasks. Empirical evidence has shown the effectiveness of LamBERTa, and also its superiority against widely used deep-learning text classifiers and a few-shot learner conceived for an attribute-aware prediction task. (shrink)

This paper puts forward a general framework for thought about human information processing. It is intended to avoid some of the problems of pipeline or stage models of function. At the same time it avoids the snare of supposing a welter of indefinitely many separate processes. The approach is not particularly original, but rather represents the common elements or presuppositions in a number of modern theories. These presuppositions are not usually explicit, however, and making them so reduces the danger of (...) slipping back into earlier modes of thought.The key point is to distinguish between persisting representations and the processes that translate one representation into another. Various classes or groups of persisting representations can be distinguished by the experimental treatments that interfere with them. In particular, there now seem to be several kinds of short-term or temporary storage, different from each other as well as from longterm memory; the translating processes also have several different modes or kinds. A particularly important aspect of the current position is that a model of this general type no longer requires some external agent to direct and control long sequences of behaviour. (shrink)

Dispositionalism about belief has had a recent resurgence. In this paper we critically evaluate a popular dispositionalist program pursued by Eric Schwitzgebel. Then we present an alternative: a psychofunctional, representational theory of belief. This theory of belief has two main pillars: that beliefs are relations to structured mental representations, and that the relations are determined by the generalizations under which beliefs are acquired, stored, and changed. We end by describing some of the generalizations regarding belief acquisition, storage, and change.

Electoral representation is a cornerstone of contemporary democracy. Democracy today is widely interpreted to mean that the people governs itself through electing officials of government. But while...

Storage operators are λ-terms which simulate call-by-value in call-by-name for a given set of terms. Krivine's storage operator theorem shows that any term of type ¬D → ¬D*, where D* is the Gödel translation of D, is a storage operator for the terms of type D when D is a data-type or a formula with only positive second order quantifiers. We prove that a new semantical version of Krivine's theorem is valid for every types. This also gives (...) a simpler proof of Krivine's theorem using the properties of data-types. (shrink)

Most nonmonotonic logics are assumed to be cumulative, which is often regarded as the minimum requirement for a logic. We argue that cumulativity, in particular, cumulative transitivity can be abandoned, in order to better characterize reasoning in uncertainty. But giving up cumulative transitivity makes it hard to obtain representation results for these logics. Borrowing the idea from strict-tolerant logics, we give some representation results for nonmonotonic logics that are not cumulatively transitive.

Early agreement within cognitive science on the topic of representation has now given way to a combination of positions. Some question the significance of representation in cognition. Others continue to argue in favor, but the case has not been demonstrated in any formal way. The present paper sets out a framework in which the value of representation use can be mathematically measured, albeit in a broadly sensory context rather than a specifically cognitive one. Key to the approach (...) is the use of Bayesian networks for modeling the distal dimension of sensory processes. More relevant to cognitive science is the theoretical result obtained, which is that a certain type of representational architecture is necessary for achievement of sensory efficiency. While exhibiting few of the characteristics of traditional, symbolic encoding, this architecture corresponds quite closely to the forms of embedded representation now being explored in some embedded/embodied approaches. It becomes meaningful to view that type of representation use as a form of information recovery. A formal basis then exists for viewing representation not so much as the substrate of reasoning and thought, but rather as a general medium for efficient, interpretive processing. (shrink)

This volume assembles leading scholars to provide a comprehensive study of representation in music from the nineteenth century to today.

The article constitutes a detailed overview of the most important background literature on the topic of scientific representation. It gives a detailed outline of many of the important philosophical accounts of scientific representation. The primary division is between substantive accounts and deflationary/pragmatic accounts. Objections to each type of account are considered. Insights from the literature on modelling are discussed along with an overview of some of the insights from the sociology of science.

This volume is a collection of new and previously published essays focusing on one of the most exciting and actively discussed topics in contemporary philosophy: naturalistic theories of mental content. The volume brings together important papers written by some of the most distinguished theorists working in the field today. Authors contributing to the volume include Jerry Fodor, Ruth Millikan, Fred Dretske, Ned Block, Robert Cummins, and Daniel Dennett.

In recent years, a number of different disciplines have begun to investigate the fundamental role context appears to play in a number of cognitive phenomena. Traditionally, linguistics, and the fields of communication and pragmatics in particular, have been the areas that have focused the most on contextual effects. Context has increasingly been studied for its role in influencing mental concepts, for some scholars being considered constitutive for most – if not all – concepts. Cognitive neuroscience is now starting to consider (...) in a systematic way how context interacts with neural responses, although this research is still scattered and concentrated in a small number of specific cases only. In this chapter, we attempt to tie these three levels together, since only from their integration can a comprehensive explanation of how context affects cognition be constructed. The way context drives language comprehension depends on the effects of context on the conceptual scaffolding of the listener, which in turn, is the result of his neural responses in combination to context. These neural responses derive from learning throughout the history of experiences of the individual, and the association between possible contexts and heard utterances. The road we take to accomplishing the multi-level integration between what appear to be distant domains, is a computational one. This approach meets with the mechanistic framework of explanation, which is currently held as the most appropriate way of approaching cognitive phenomena that is often characterized by a multiplicity of levels, as is the case with context. The core underlying concept of the neurocomputational framework here proposed, is an account of neural representation, based on structural similarity. Structural representations are still the best option on the market in cognitive science, but in their traditional form, derived from classical measurement theory, are affected by a number of serious drawbacks, including not being able to account for context. We suggest a different account of structural similarity, one informed by current neuroscience, where the homomorphic relations required for structural similarity are derived from neural population coding. In a preliminary mathematical sketch, we indicate how this approach can construct neural aggegations that are sensitive to context. (shrink)

Advocates of the computational theory of mind claim that the mind is a computer whose operations can be implemented by various computational systems. According to these philosophers, the mind is multiply realisable because—as they claim—thinking involves the manipulation of syntactically structured mental representations. Since syntactically structured representations can be made of different kinds of material while performing the same calculation, mental processes can also be implemented by different kinds of material. From this perspective, consciousness plays a minor role in mental (...) activity. However, contemporary neuroscience provides experimental evidence suggesting that mental representations necessarily involve consciousness. Consciousness does not only enable individuals to become aware of their own thoughts, it also constantly changes the causal properties of these thoughts. In light of these empirical studies, mental representations appear to be intrinsically dependent on consciousness. This discovery represents an obstacle to any attempt to construct an artificial mind. (shrink)

The never ending growth of digital information and the availability of low-cost storage facilities and networks capacity is leading users towards moving their data to remote storage resources. Since users’ data often holds identity-related information, several privacy issues arise when data can be stored in untrusted domains. In addition digital identity management is becoming extremely complicated due to the identity replicas proliferation necessary to get authentication in different domains. GMail and Amazon Web Services, for instance, are two examples (...) of online services adopted by million of users throughout the world which hold huge amounts of sensitive users data. State-of-the-art encryption tools for large-scale distributed infrastructures allow users to encrypt content locally before storing it on a remote untrusted repository. This approach can experience performance drawbacks, when very large data-sets must be encrypted/decrypted on a single machine. The proposed approach extends the existing solutions by providing two additional features: (1) the encryption can also be delegated to a pool of remote trusted computing resources, and (2) the definition of the encryption context which drives the tool to select the best strategy to process the data. The performance benchmarks are based on the results of tests carried out both on a local workstation and on the Grid INFN Laboratory for Dissemination Activities (GILDA) testbed. (shrink)

Following the concept of internal representations, signal processing in a neuronal system has to be evaluated exclusively on the basis of internal system characteristics. Thus, this approach omits the external observer as a control function for sensory integration. Instead, the configuration of the system and its computational performance are the effects of endogeneous factors. Such self-referential operation is due to a strictly local computation in a network. Thereby, computations follow a set of rules that constitutes the emergent behaviour of the (...) system. Because these rules can be demonstrated to correspond to a "logic" intrinsic to the system, it can be shown that the concept of internal representation provides the basis for neurosemantics. (shrink)

Miller (1956) summarized evidence that people can remember about seven chunks in short-term memory (STM) tasks. However, that number was meant more as a rough estimate and a rhetorical device than as a real capacity limit. Others have since suggested that there is a more precise capacity limit, but that it is only three to five chunks. The present target article brings together a wide variety of data on capacity limits suggesting that the smaller capacity limit is real. Capacity limits (...) will be useful in analyses of information processing only if the boundary conditions for observing them can be carefully described. Four basic conditions in which chunks can be identified and capacity limits can accordingly be observed are: (1) when information overload limits chunks to individual stimulus items, (2) when other steps are taken specifically to block the recoding of stimulus items into larger chunks, (3) in performance discontinuities caused by the capacity limit, and (4) in various indirect effects of the capacity limit. Under these conditions, rehearsal and long-term memory cannot be used to combine stimulus items into chunks of an unknown size; nor can storage mechanisms that are not capacity-limited, such as sensory memory, allow the capacity-limited storage mechanism to be refilled during recall. A single, central capacity limit averaging about four chunks is implicated along with other, noncapacity-limited sources. The pure STM capacity limit expressed in chunks is distinguished from compound STM limits obtained when the number of separately held chunks is unclear. Reasons why pure capacity estimates fall within a narrow range are discussed and a capacity limit for the focus of attention is proposed. Key Words: attention; enumeration; information chunks; memory capacity; processing capacity; processing channels; serial recall; short-term memory; storage capacity; verbal recall; working memory capacity. (shrink)

This book is not a conventional introduction to the philosophy of mind, nor is it a contribution to the physicalist/ dualist debate. Instead The Representational Theory of Mind demonstrates that we can construct physicalist theories of important aspects of our mental life. Its aim is to explain and defend a physicalist theory of intelligence in two parts: the first six chapters consist of an exposition, elaboration and defence of human sentience (the functionalist theory of mind), and the second part considers (...) rivals and objections to this theory. Kim Sterelny aims to introduce people to this area of philosophy by exemplifying it, to show that philosophical and empirical investigations can be synthesized to the benefit of both. --From publisher's description. (shrink)