Roland Hausser - Böcker

The book gives a comprehensive discussion of Database Semantics (DBS) as an agent-based data-driven theory of how natural language communication essentially works. In language communication, agents switch between speak mode, driven by cognition-internal content (input) resulting in cognition-external raw data (e.g. sound waves or pixels, which have no meaning or grammatical properties but can be measured by natural science), and hear mode, driven by the raw data produced by the speaker resulting in cognition-internal content.The motivation is to compare two approaches for an ontology of communication: agent-based data-driven vs. sign-based substitution-driven. Agent-based means: design of a cognitive agent with (i) an interface component for converting raw data into cognitive content (recognition) and converting cognitive content into raw data (action), (ii) an on-board, content-addressable memory (database) for the storage and content retrieval, (iii) separate treatments of the speak and the hear mode. Data-driven means: (a) mapping a cognitive content as input to the speak-mode into a language-dependent surface as output, (b) mapping a surface as input to the hear-mode into a cognitive content as output. Oppositely, sign-based means: no distinction between speak and hear mode, whereas substitution-driven means: using a single start symbol as input for generating infinitely many outputs, based on substitutions by rewrite rules.Collecting recent research of the author, this beautiful, novel and original exposition begins with an introduction to DBS, makes a linguistic detour on subject/predicate gapping and slot-filler repetition, and moves on to discuss computational pragmatics, inference and cognition, grammatical disambiguation and other related topics. The book is mostly addressed to experts working in the field of computational linguistics, as well as toenthusiasts interested in the history and early development of this subject, starting with the pre-computational foundations of theoretical computer science and symbolic logic in the 30s.

The book gives a comprehensive discussion of Database Semantics (DBS) as an agent-based data-driven theory of how natural language communication essentially works. In language communication, agents switch between speak mode, driven by cognition-internal content (input) resulting in cognition-external raw data (e.g. sound waves or pixels, which have no meaning or grammatical properties but can be measured by natural science), and hear mode, driven by the raw data produced by the speaker resulting in cognition-internal content.The motivation is to compare two approaches for an ontology of communication: agent-based data-driven vs. sign-based substitution-driven. Agent-based means: design of a cognitive agent with (i) an interface component for converting raw data into cognitive content (recognition) and converting cognitive content into raw data (action), (ii) an on-board, content-addressable memory (database) for the storage and content retrieval, (iii) separate treatments of the speak and the hear mode. Data-driven means: (a) mapping a cognitive content as input to the speak-mode into a language-dependent surface as output, (b) mapping a surface as input to the hear-mode into a cognitive content as output. Oppositely, sign-based means: no distinction between speak and hear mode, whereas substitution-driven means: using a single start symbol as input for generating infinitely many outputs, based on substitutions by rewrite rules.Collecting recent research of the author, this beautiful, novel and original exposition begins with an introduction to DBS, makes a linguistic detour on subject/predicate gapping and slot-filler repetition, and moves on to discuss computational pragmatics, inference and cognition, grammatical disambiguation and other related topics. The book is mostly addressed to experts working in the field of computational linguistics, as well as toenthusiasts interested in the history and early development of this subject, starting with the pre-computational foundations of theoretical computer science and symbolic logic in the 30s.

Modern science is divided into three parts: natural sciences, engineering sciences and humanities. Over the last millennia, natural and engineering sciences evolved a symbiotic relationship, but humanities still stand apart. Today, however, designing and building a talking robot is a comparatively new challenge for which all three branches are needed. Starting from the idea that designing a theory of computational cognition should be as complete as possible, and trying to answer questions such as “Which ontology is required for building a computational cognition?”, the current book integrates interfaces, components, functional flows, data structure, database schema, and algorithms into a coherent system with an extensive range of cognitive functions, and constitutes the background to the book “Ontology of Communication” recently published by the author (Springer, 2023).Part I discusses ontological distinctions between a sign-based and an agent-based approach, and continues with explanations of the data structure, the content-addressable database schema; the time-linear derivations of the speak and the hear mode; resonating content; induction, deduction, and abduction in inferencing, and concludes with a reconstruction of eight classical syllogisms as a test suite for DBS inferencing in the think mode. Part II complements the literal use of language in the speak and hear mode with a reconstruction of syntactic mood adaptations and figurative use. The database schema of DBS is shown to lend itself not only to the tasks of traditional storage and retrieval, but also of reference, coreference, shadowing, coactivation of resonating content, and selective activation.Part III complements the treatment of individual topics in linguistics, philosophy, and cognitive psychology with an overall software structure in the form of three interacting main components, called the interface, the memory, and the production component.

Modern science is divided into three parts: natural sciences, engineering sciences and humanities. Over the last millennia, natural and engineering sciences evolved a symbiotic relationship, but humanities still stand apart. Today, however, designing and building a talking robot is a comparatively new challenge for which all three branches are needed. Starting from the idea that designing a theory of computational cognition should be as complete as possible, and trying to answer questions such as “Which ontology is required for building a computational cognition?”, the current book integrates interfaces, components, functional flows, data structure, database schema, and algorithms into a coherent system with an extensive range of cognitive functions, and constitutes the background to the book “Ontology of Communication” recently published by the author (Springer, 2023).Part I discusses ontological distinctions between a sign-based and an agent-based approach, and continues with explanations of the data structure, the content-addressable database schema; the time-linear derivations of the speak and the hear mode; resonating content; induction, deduction, and abduction in inferencing, and concludes with a reconstruction of eight classical syllogisms as a test suite for DBS inferencing in the think mode. Part II complements the literal use of language in the speak and hear mode with a reconstruction of syntactic mood adaptations and figurative use. The database schema of DBS is shown to lend itself not only to the tasks of traditional storage and retrieval, but also of reference, coreference, shadowing, coactivation of resonating content, and selective activation.Part III complements the treatment of individual topics in linguistics, philosophy, and cognitive psychology with an overall software structure in the form of three interacting main components, called the interface, the memory, and the production component.

This book explains how to use ideas from computer science, linguistics, philosophy, psychology, artificial intelligence, and cybernetics to build a talking robot. The author's own system, Database Semantics (DBS), provides the required cycle of natural language communication, and cybernetics and artificial intelligence techniques are used to design an autonomous control system. The book will be of particular value to researchers in linguistics, artificial intelligence, and cybernetics.

The practical task of building a talking robot requires a theory of how natural language communication works. Conversely, the best way to computationally verify a theory of natural language communication is to demonstrate its functioning concretely in the form of a talking robot, the epitome of human–machine communication. To build an actual robot requires hardware that provides appropriate recognition and action interfaces, and because such hardware is hard to develop the approach in this book is theoretical: the author presents an artificial cognitive agent with language as a software system called database semantics (DBS). Because a theoretical approach does not have to deal with the technical difficulties of hardware engineering there is no reason to simplify the system – instead the software components of DBS aim at completeness of function and of data coverage in word form recognition, syntactic–semantic interpretation and inferencing, leaving the procedural implementation of elementary concepts for later. In this book the author first examines the universals of natural language and explains the Database Semantics approach. Then in Part I he examines the following natural language communication issues: using external surfaces; the cycle of natural language communication; memory structure; autonomous control; and learning. In Part II he analyzes the coding of content according to the aspects: semantic relations of structure; simultaneous amalgamation of content; graph-theoretical considerations; computing perspective in dialogue; and computing perspective in text. The book ends with a concluding chapter, a bibliography and an index. The book will be of value to researchers, graduate students and engineers in the areas of artificial intelligence and robotics, in particular those who deal with natural language processing.

The content of this textbook is organized as a theory of language for the construction of talking robots.

The practical task of building a talking robot requires a theory of how natural language communication works. Conversely, the best way to computationally verify a theory of natural language communication is to demonstrate its functioning concretely in the form of a talking robot, the epitome of human–machine communication. To build an actual robot requires hardware that provides appropriate recognition and action interfaces, and because such hardware is hard to develop the approach in this book is theoretical: the author presents an artificial cognitive agent with language as a software system called database semantics (DBS). Because a theoretical approach does not have to deal with the technical difficulties of hardware engineering there is no reason to simplify the system – instead the software components of DBS aim at completeness of function and of data coverage in word form recognition, syntactic–semantic interpretation and inferencing, leaving the procedural implementation of elementary concepts for later. In this book the author first examines the universals of natural language and explains the Database Semantics approach. Then in Part I he examines the following natural language communication issues: using external surfaces; the cycle of natural language communication; memory structure; autonomous control; and learning. In Part II he analyzes the coding of content according to the aspects: semantic relations of structure; simultaneous amalgamation of content; graph-theoretical considerations; computing perspective in dialogue; and computing perspective in text. The book ends with a concluding chapter, a bibliography and an index. The book will be of value to researchers, graduate students and engineers in the areas of artificial intelligence and robotics, in particular those who deal with natural language processing.

The study of linguistics has been forever changed by the advent of the computer. Not only does the machine permit the processing of enormous quantities of text­ thereby securing a better empirical foundation for conclusions-but also, since it is a modelling device, the machine allows the implementation of theories of grammar and other kinds of language processing. Models can have very unexpected properties­ both good and bad-and it is only through extensive tests that the value of a model can be properly assessed. The computer revolution has been going on for many years, and its importance for linguistics was recognized early on, but the more recent spread of personal workstations has made it a reality that can no longer be ignored by anyone in the subject. The present essay, in particular, could never have been written without the aid of the computer. I know personally from conversations and consultations with the author over many months how the book has changed. If he did not have at his command a powerful typesetting program, he would not have been able to see how his writing looked and exactly how it had to be revised and amplified. Even more significant for the evolution of the linguistic theory is the easy testing of examples made possible by the implementation of the parser and the computer-held lexicon. Indeed, the rule set and lexicon grew substantially after the successes of the early implementations created the desire to incorporate more linguistic phenomena.