How is it that many schizophrenics identify certain instances of verbal imagery as hallucinatory? Most investigators have assumed that alterations in sensory features of imagery explain this. This approach, however, has not yielded a definitive picture of the nature of verbal hallucinations. An alternative perspective suggests itself if one allows the possibility that the nonself quality of hallucinations is inferred on the basis of the experience of unintendedness that accompanies imagery production. Information-processing models of “intentional” cognitive processes call for abstract (...) planning representations that are linked to goals and beliefs. Unintended actions - and imagery - can reflect planning disruptions whereby cognitive products do not cohere with concurrent goals. A model of schizophrenic speech disorganization is presented that postulates a disturbance of discourse planning. Insofar as verbal imagery can be viewed as inwardly directed speech, a consequence of such planning disturbances could be the production of unintended imagery. This link between the outward disorganization of schizophrenic speech and unintended verbal imagery is statistically supported by comparing the speech behavior of hallucinating and nonhallucinating schizophrenics. Studies of “borderline” hallucinations during normal, “goal-less” relaxation and drowsiness suggest that experiential unintendedness leads to a nonpathological variant of hallucinatory otherness that is correctable upon emerging from such passive cognitive states. This contrasts with the schizophrenic case, where nonconcordance with cognitive goals reinforces the unintendedness of verbal images and sustains the conviction of an external source. This model compares favorably with earlier models of verbal hallucinations and provides further evidence for a language production disorder in many schizophrenics.Short Abstract: How is it that many schizophrenics identify certain instances of verbal imagery as hallucinatory? This paper proposes that the critical feature identifying hallucinations is the experience of unintendedness. This experience is nonpathological during passive conscious states but pathological if occurring during goal-directed cognitive processing. A model of schizophrenic speech disorganization is presented that postulates a disturbance of discourse planning that specifies communicative intentions. These alterations could generate unintended verbal imagery as well. Statistical data are offered to support the model, and relevant empirical studies are reviewed. (shrink)

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 (...) S&A's system (amongst many other connectionist systems, recognizing that S&A's is much more capable as regards reasoning than most other contemporary systems). (shrink)

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.

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 (...) human-computer interaction are also suggested. (shrink)

This project continues our interdisciplinary research into computational and cognitive aspects of narrative comprehension. Our ultimate goal is the development of a computational theory of how humans understand narrative texts. The theory will be informed by joint research from the viewpoints of linguistics, cognitive psychology, the study of language acquisition, literary theory, geography, philosophy, and artificial intelligence. The linguists, literary theorists, and geographers in our group are developing theories of narrative language and spatial understanding that are being tested by the (...) cognitive psychologists and language researchers in our group, and a computational model of a reader of narrative text is being developed by the AI researchers, based in part on these theories and results and in part on research on knowledge representation and reasoning. This proposal describes the knowledge-representation and natural-language-processing issues involved in the computational implementation of the theory; discusses a contrast between communicative and narrative uses of language and of the relation of the narrative text to the story world it describes; investigates linguistic, literary, and hermeneutic dimensions of our research; presents a computational investigation of subjective sentences and reference in narrative; studies children’s acquisition of the ability to take third-person perspective in their own storytelling; describes the psychological validation of various linguistic devices; and examines how readers develop an understanding of the geographical space of a story. This report is a longer version of a project description submitted to NSF. This document, produced in May 2007, is a L ATEX version of Technical Report 89-07 (Buffalo: SUNY Buffalo Department of Computer Science, August 1989), with slightly.. (shrink)

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, (...) the essay analyzes Keller’s belief that learning that “everything has a name” was the key to her success, enabling her to “partition” her mental concepts into mental representations of: words, objects, and the naming relations between them. It next looks at Herbert Terrace’s theory of naming, which is akin to Keller’s, and which only humans are supposed to be capable of. The essay suggests that computers at least, and perhaps non-human primates, are also capable of this kind of naming. (shrink)

In this article a discourse is regarded as a verbalization of some interactive cognitive process which may be represented in form of a logical-cognitive scheme as a model of this discourse. Such model is elaborated on the ground of logical-cognitive theory of practical reasoning by using the definitions of analytical rules for construing model sets. The discourse 's formal language is defined and takes into account the significance of quest schemes which are included in different kinds of intensional contexts of (...) discourse expressions. The discourse model is described in terms of cognitive interpretations which determine conditions of the actualization of cognitive events as elements of the discourse semantic. The pecularities of this model are explalned by deciding one cognitive riddle. (shrink)

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 (...) describe a minimal logic for intentions and beliefs that is sound and complete relative to our semantics. We discuss several additional axioms, and the constraints on the models that validate them. (shrink)

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 (...) by intentions [7, 9], and shows how agents can avoid intending all the foreseen side-effects of what they actually intend. Finally, the analysis shows how intentions can be adopted relative to a background of relevant beliefs and other intentions or goals. By relativizing one agent's intentions in terms of beliefs about another agent's intentions (or beliefs'), we derive a preliminary account of interpersonal commitments. (shrink)

An integrated statement is made concerning the semantic status of nodes in a propositional semantic network, claiming that such nodes represent only intensions. Within the network, the only reference to extensionality is via a mechanism to assert that two intensions have the same extension in same world. This framework is employed in three application problems to illustrate the nature of its solutions.The formalism used here utilizes only assertional information and no structural, or definitional, information. This restriction corresponds to many of (...) the psychologically motivated network models. Some of the psychological implications of network processes called node merging and node splitting are discussed. Additionally, it is pointed out that both our networks and the psychologically based networks are prone to memory confusions about knowing unless augmented by domain‐specific inference processes, or by structural information. (shrink)

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 (...) to account (from an `internal', or first-person perspective) for how a cognitive agent understands language. Some have argued for the primacy of external, or `wide', semantics, while others have argued for a two-factor analysis. But, although two factors can be specified–-one internal and first-person, the other only specifiable in an external, third-person way–-only the internal, first-person one is needed for understanding how someone understands. A truth-conditional semantics can still be provided, but only from a third-person perspective. (shrink)

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 (...) of inference of implied information, reasoning from generalizations, and meta-reasoning, challenges AI practitioners have wrestled with since at least 1980 and continue to study. We argue that the very fact the Imitation Game is so difficult may be the very reason it shouldn’t be changed or abandoned. The semi-decidability of the game at this point hints at the possibility of a hard limit to the powers of technology. (shrink)

We introduce a computational theory of situated language understanding in which the meaning of words and utterances depends on the physical environment and the goals and plans of communication partners. According to the theory, concepts that ground linguistic meaning are neither internal nor external to language users, but instead span the objective‐subjective boundary. To model the possible interactions between subject and object, the theory relies on the notion of perceived affordances: structured units of interaction that can be used for prediction (...) at multiple levels of abstraction. Language understanding is treated as a process of filtering perceived affordances. The theory accounts for many aspects of the situated nature of human language use and provides a unified solution to a number of demands on any theory of language understanding including conceptual combination, prototypicality effects, and the generative nature of lexical items.To support the theory, we describe an implemented system that understands verbal commands situated in a virtual gaming environment. The implementation uses probabilistic hierarchical plan recognition to generate perceived affordances. The system has been evaluated on its ability to correctly interpret free‐form spontaneous verbal commands recorded from unrehearsed game play between human players. The system is able to “step into the shoes” of human players and correctly respond to a broad range of verbal commands in which linguistic meaning depends on social and physical context. We quantitatively compare the system's predictions in response to direct player commands with the actions taken by human players and show generalization to unseen data across a range of situations and verbal constructions. (shrink)

In order to be capable of exhibiting a wide range of cooperative behavior, a computer-based dialog system must have available assumptions about the current user's goals, plans, background knowledge and (false) beliefs, i.e., maintain a so-called “user model”. Apart from cooperativity aspects, such a model is also necessary for intelligent coherent dialog behavior in general. This article surveys recent research on the problem of how such a model can be constructed, represented and used by a system during its interaction with (...) the user. Possible applications, as well as potential problems concerning the advisability of application, are then discussed. Finally, a number of guidelines are presented which should be observed in future research to reduce the risk of a potential misuse of user modeling technology. (shrink)

In this paper, we claim that the disambiguation ofreferring expressions in discourse can be formulated in terms automatedreasoners can address. Specifically, we show that consistency,informativity and minimality are criteria which (i) can be implementedusing automated reasoning tools and (ii) can be used to disambiguatenoun-noun compounds, metonymy and definite descriptions.

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 (...) see the processing of information in the conversation to be dependent upon which point classification the user decides upon. (shrink)

This research is concerned with the innate predispositions underlying human intentional communication. Human communication is currently defined as a circular and overt attempt to modify a partner's mental states. This requires each party involved to posse ss the ability to represent and understand the other's mental states, a capability which is commonly referred to as mindreading, or theory of mind (ToM). The relevant experimental literature agrees that no such capability is to be found in the human speci es at least (...) during the first year of life, and possibly later. This paper aims at advancing a solution to this theoretical problem. We propose to consider sharedness as the basis for intentional communication in the infant and to view it as a primitive, i nnate component of her cognitive architecture. Communication can then build upon the mental grounds that the infant takes as shared with her caregivers. We view this capability as a theory of mind in a weak sense.›. (shrink)

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 (...) body of systemic knowledge and perform a range of inferences with such speed? We describe a computational model that takes a step toward addressing the cognitive science challenge and resolving the artificial intelligence paradox. We show how a connectionist network can encode millions of facts and rules involving n-ary predicates and variables and perform a class of inferences in a few hundred milliseconds. Efficient reasoning requires the rapid representation and propagation of dynamic bindings. Our model (which we refer to as SHRUTI) achieves this by representing (1) dynamic bindings as the synchronous firing of appropriate nodes, (2) rules as interconnection patterns that direct the propagation of rhythmic activity, and (3) long-term facts as temporal pattern-matching subnetworks. The model is consistent with recent neurophysiological evidence that synchronous activity occurs in the brain and may play a representational role in neural information processing. The model also makes specific psychologically significant predictions about the nature of reflexive reasoning. It identifies constraints on the form of rules that may participate in such reasoning and relates the capacity of the working memory underlying reflexive reasoning to biological parameters such as the lowest frequency at which nodes can sustain synchronous oscillations and the coarseness of synchronization. (shrink)