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  1. Situated Utterances and Discourse Relations.Ernest Lepore, Una Stojnic & Matthew Stone - 2013 - In Ernest Lepore, Una Stojnic & Matthew Stone (eds.), Proceedings of the 10 th International Conference on Computational Semantics. Potsdam: IWCS. pp. 390 – 396.
    Utterances in situated activity are about the world. Theories and systems normally capture this by assuming references must be resolved to real-world entities in utterance understanding. We describe a number of puzzles and problems for this approach, and propose an alternative semantic representation using discourse relations that link utterances to the nonlinguistic context to capture the context-dependent interpretation of situated utterances. Our approach promises better empirical coverage and more straightforward system building. Substantiating these advantages is work in progress.
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  • Reality and control.James Deese - 1986 - Behavioral and Brain Sciences 9 (3):521-522.
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  • Making a middling mousetrap.Michael R. W. Dawson & Istvan Berkeley - 1993 - Behavioral and Brain Sciences 16 (3):454-455.
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  • From symbols to neurons: Are we there yet?Garrison W. Cottrell - 1993 - Behavioral and Brain Sciences 16 (3):454-454.
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  • Could static binding suffice?Paul R. Cooper - 1993 - Behavioral and Brain Sciences 16 (3):453-454.
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  • Intention is choice with commitment.Philip R. Cohen & Hector J. Levesque - 1990 - Artificial Intelligence 42 (2-3):213-261.
    This paper explores principles governing the rational balance among an agent's beliefs, goals, actions, and intentions. Such principles provide specifications for artificial agents, and approximate a theory of human action (as philosophers use the term). By making explicit the conditions under which an agent can drop his goals, i.e., by specifying how the agent is committed to his goals, the formalism captures a number of important properties of intention. Specifically, the formalism provides analyses for Bratman's three characteristic functional roles played (...)
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  • Prescribed mental attitudes in goal-adoption and Norm-adoption.Cristiano Castelfranchi - 1999 - Artificial Intelligence and Law 7 (1):37-50.
    The general aim of this work is to show the importance of the adressee's mind as planned by the author of a speech act or of a norm; in particular, how important are the expected motivations for goal adoption. We show that speech acts differ from one another for the different motivations the speaker is attempting to obtain from the hearer. The description of the participants' social positions is not sufficient. Important conflicts can arise which are not relative to what (...)
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  • Intended versus intentional action.Myles Brand - 1986 - Behavioral and Brain Sciences 9 (3):520-521.
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  • Verbal hallucinations, unintendedness, and the validity of the schizophrenia diagnosis.R. P. Bentall & P. D. Slade - 1986 - Behavioral and Brain Sciences 9 (3):519-520.
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  • Plausible inference and implicit representation.Malcolm I. Bauer - 1993 - Behavioral and Brain Sciences 16 (3):452-453.
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  • Time phases, pointers, rules and embedding.John A. Barnden - 1993 - Behavioral and Brain Sciences 16 (3):451-452.
    This paper is a commentary on the target article by Lokendra Shastri & Venkat Ajjanagadde [S&A]: “From simple associations to systematic reasoning: A connectionist representation of rules, variables and dynamic bindings using temporal synchrony” in same issue of the journal, pp.417–451. -/- It puts S&A's temporal-synchrony binding method in a broader context, comments on notions of pointing and other ways of associating information - in both computers and connectionist systems - and mentions types of reasoning that are a challenge to (...)
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  • Planning english referring expressions.Douglas E. Appelt - 1985 - Artificial Intelligence 26 (1):1-33.
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  • Language process and hallucination phenomenology.Murray Alpert - 1986 - Behavioral and Brain Sciences 9 (3):518-519.
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  • Towards a general theory of action and time.James F. Allen - 1984 - Artificial Intelligence 23 (2):123-154.
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  • A three-component analysis of Hoffman's model of verbal hallucinations.Heidelinde Allen - 1986 - Behavioral and Brain Sciences 9 (3):518-518.
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  • Who may I say is calling?Kathleen A. Akins & Daniel C. Dennett - 1986 - Behavioral and Brain Sciences 9 (3):517-518.
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  • Synchronization and cognitive carpentry: From systematic structuring to simple reasoning. E. Koerner - 1993 - Behavioral and Brain Sciences 16 (3):465-466.
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  • Image or neural coding of inner speech and agency?Gail Zivin - 1986 - Behavioral and Brain Sciences 9 (3):534-535.
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  • Ethereal oscillations.Malcolm P. Young - 1993 - Behavioral and Brain Sciences 16 (3):476-477.
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  • Motivating non-canonicality in Construction Grammar: The case of locative inversion.Gert Webelhuth - 2011 - Cognitive Linguistics 22 (1):81-105.
    This article discusses the English construction variously known as Locative Inversion or Stylistic Inversion. It shows that the construction displays a unique ensemble of grammatical and usage properties that can be stated but not motivated through purely grammatical means. In search of an explanatory approach, an analysis is presented that draws on concepts of Artificial Intelligence, in particular plans viewed as complex mental attitudes. It is claimed that utterances of Locative Inversion are associated with a particular communicative plan on the (...)
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  • The effect of resource limits and task complexity on collaborative planning in dialogue.Marilyn A. Walker - 1996 - Artificial Intelligence 85 (1-2):181-243.
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  • Toward a Computational Psycholinguistics of Reference Production.Kees van Deemter, Albert Gatt, Roger P. G. van Gompel & Emiel Krahmer - 2012 - Topics in Cognitive Science 4 (2):166-183.
    This article introduces the topic ‘‘Production of Referring Expressions: Bridging the Gap between Computational and Empirical Approaches to Reference’’ of the journal Topics in Cognitive Science. We argue that computational and psycholinguistic approaches to reference production can benefit from closer interaction, and that this is likely to result in the construction of algorithms that differ markedly from the ones currently known in the computational literature. We focus particularly on determinism, the feature of existing algorithms that is perhaps most clearly at (...)
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  • Dynamic-binding theory is not plausible without chaotic oscillation.Ichiro Tsuda - 1993 - Behavioral and Brain Sciences 16 (3):475-476.
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  • Should first-order logic be neurally plausible?David S. Touretzky & Scott E. Fahlman - 1993 - Behavioral and Brain Sciences 16 (3):474-475.
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  • Temporal synchrony and the speed of visual processing.Simon J. Thorpe - 1993 - Behavioral and Brain Sciences 16 (3):473-474.
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  • Phase logic is biologically relevant logic.Gary W. Strong - 1993 - Behavioral and Brain Sciences 16 (3):472-473.
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  • Intention, interpretation and the computational structure of language.Matthew Stone - 2004 - Cognitive Science 28 (5):781-809.
    I show how a conversational process that takes simple, intuitively meaningful steps may be understood as a sophisticated computation that derives the richly detailed, complex representations implicit in our knowledge of language. To develop the account, I argue that natural language is structured in a way that lets us formalize grammatical knowledge precisely in terms of rich primitives of interpretation. Primitives of interpretation can be correctly viewed intentionally, as explanations of our choices of linguistic actions; the model therefore fits our (...)
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  • Hallucinations and contextually generated interpretations.Nicholas P. Spanos - 1986 - Behavioral and Brain Sciences 9 (3):533-534.
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  • Do simple associations lead to systematic reasoning?Steven Sloman - 1993 - Behavioral and Brain Sciences 16 (3):471-472.
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  • A logic of intentions and beliefs.Munindar P. Singh & Nicholas M. Asher - 1993 - Journal of Philosophical Logic 22 (5):513 - 544.
    Intentions are an important concept in Artificial Intelligence and Cognitive Science. We present a formal theory of intentions and beliefs based on Discourse Representation Theory that captures many of their important logical properties. Unlike possible worlds approaches, this theory does not assume that agents are perfect reasoners, and gives a realistic view of their internal architecture; unlike most representational approaches, it has an objective semantics, and does not rely on an ad hoc labeling of the internal states of agents. We (...)
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  • From simple associations to systematic reasoning: A connectionist representation of rules, variables, and dynamic binding using temporal synchrony.Lokendra Shastri & Venkat Ajjanagadde - 1993 - Behavioral and Brain Sciences 16 (3):417-51.
    Human agents draw a variety of inferences effortlessly, spontaneously, and with remarkable efficiency – as though these inferences were a reflexive response of their cognitive apparatus. Furthermore, these inferences are drawn with reference to a large body of background knowledge. This remarkable human ability seems paradoxical given the complexity of reasoning reported by researchers in artificial intelligence. It also poses a challenge for cognitive science and computational neuroscience: How can a system of simple and slow neuronlike elements represent a large (...)
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  • A step toward modeling reflexive reasoning.Lokendra Shastri & Venkat Ajjanagadde - 1993 - Behavioral and Brain Sciences 16 (3):477-494.
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  • What's the Point?Roger C. Schank, Gregg C. Collins, Ernest Davis, Peter N. Johnson, Steve Lytinen & Brian J. Reiser - 1982 - Cognitive Science 6 (3):255-275.
    We present a theory of conversation comprehension in which a line of the conversation is “understood” by relating it to one of seven possible “points”. We define these points, and present examples where it seems plausible that the failure to “get the point” would indeed constitute a failure to understand the conversation. We argue that the recognition of such points must proceed in both a top down and bottom up fashion, and thus is likely to be quite complicated. Finally, we (...)
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  • Hallucination, rationalization, and response set.Steven Schwartz - 1986 - Behavioral and Brain Sciences 9 (3):532-533.
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  • Verbal hallucinations and information processing.Bjørn Rishovd Rund - 1986 - Behavioral and Brain Sciences 9 (3):531-532.
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  • Useful ideas for exploiting time to engineer representations.Richard Rohwer - 1993 - Behavioral and Brain Sciences 16 (3):471-471.
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  • When is an image hallucinatory?Graham F. Reed - 1986 - Behavioral and Brain Sciences 9 (3):530-531.
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  • How Helen Keller Used Syntactic Semantics to Escape from a Chinese Room.William J. Rapaport - 2006 - Minds and Machines 16 (4):381-436.
    A computer can come to understand natural language the same way Helen Keller did: by using “syntactic semantics”—a theory of how syntax can suffice for semantics, i.e., how semantics for natural language can be provided by means of computational symbol manipulation. This essay considers real-life approximations of Chinese Rooms, focusing on Helen Keller’s experiences growing up deaf and blind, locked in a sort of Chinese Room yet learning how to communicate with the outside world. Using the SNePS computational knowledge-representation system, (...)
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  • Holism, conceptual-role semantics, and syntactic semantics.William J. Rapaport - 2002 - Minds and Machines 12 (1):3-59.
    This essay continues my investigation of `syntactic semantics': the theory that, pace Searle's Chinese-Room Argument, syntax does suffice for semantics (in particular, for the semantics needed for a computational cognitive theory of natural-language understanding). Here, I argue that syntactic semantics (which is internal and first-person) is what has been called a conceptual-role semantics: The meaning of any expression is the role that it plays in the complete system of expressions. Such a `narrow', conceptual-role semantics is the appropriate sort of semantics (...)
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  • Verbal hallucinations also occur in normals.Thomas B. Posey - 1986 - Behavioral and Brain Sciences 9 (3):530-530.
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  • Making reasoning more reasonable: Event-coherence and assemblies.Günther Palm - 1993 - Behavioral and Brain Sciences 16 (3):470-470.
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  • Psychological implications of the synchronicity hypothesis.Stellan Ohlsson - 1993 - Behavioral and Brain Sciences 16 (3):469-469.
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  • Intentions in communication.Jon Oberlander - 1993 - Artificial Intelligence 63 (1-2):511-520.
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  • Computational and biological constraints in the psychology of reasoning.Mike Oaksford & Mike Malloch - 1993 - Behavioral and Brain Sciences 16 (3):468-469.
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  • Imitation Game: Threshold or Watershed?Eric Neufeld & Sonje Finnestad - 2020 - Minds and Machines 30 (4):637-657.
    Showing remarkable insight into the relationship between language and thought, Alan Turing in 1950 proposed the Imitation Game as a proxy for the question “Can machines think?” and its meaning and practicality have been debated hotly ever since. The Imitation Game has come under criticism within the Computer Science and Artificial Intelligence communities with leading scientists proposing alternatives, revisions, or even that the Game be abandoned entirely. Yet Turing’s imagined conversational fragments between human and machine are rich with complex instances (...)
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  • What we know and the LTKB.Stanley Munsat - 1993 - Behavioral and Brain Sciences 16 (3):466-467.
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  • Distributed artificial intelligence from a socio-cognitive standpoint: Looking at reasons for interaction. [REVIEW]Maria Miceli, Amedo Cesta & Paola Rizzo - 1995 - AI and Society 9 (4):287-320.
    Distributed Artificial Intelligence (DAI) deals with computational systems where several intelligent components interact in a common environment. This paper is aimed at pointing out and fostering the exchange between DAI and cognitive and social science in order to deal with the issues of interaction, and in particular with the reasons and possible strategies for social behaviour in multi-agent interaction is also described which is motivated by requirements of cognitive plausibility and grounded the notions of power, dependence and help. Connections with (...)
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  • Discourse strategies for generating natural-language text.Kathleen R. McKeown - 1985 - Artificial Intelligence 27 (1):1-41.
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  • Reflections on reflexive reasoning.David L. Martin - 1993 - Behavioral and Brain Sciences 16 (3):466-466.
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  • Intentionality and autonomy of verbal imagery in altered states of consciousness.David F. Marks - 1986 - Behavioral and Brain Sciences 9 (3):529-530.
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