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In the not so distant future, we can expect a world where humans and robots coexist and interact with each other. For this to occur, we need to understand human traits, such as seeing, hearing, thinking, speaking, etc., and institute these traits in robots. The most essential feature necessary for robots to achieve is that of integrative multimedia understanding (IMU) which occurs naturally in humans. It allows us to assimilate pieces of information expressed through different modes such as speech, pictures, gestures, etc.
The book describes how robots acquire traits like natural language understanding (NLU) as the central part of IMU. Mental image directed semantic theory (MIDST) is its core, and is based on the hypothesis that NLU is essentially the processing of mental image associated with natural language expressions, namely, mental-image based understanding (MBU). MIDST is intended to model omnisensory mental image in human and to afford a knowledge representation system in order for integrative management of knowledge subjective to cognitive mechanisms of intelligent entities such as humans and robots based on a mental image model visualized as 'Loci in Attribute Spaces' and its description language Lmd (mental image description language) to be employed for predicate logic with a systematic scheme for symbol-grounding. This language works as an interlingua among various kinds of information media, and has been applied to several versions of the intelligent system interlingual understanding model aiming at general system (IMAGES). Its latest version, i.e. conversation management system (CMS) simulates MBU and comprehends the user's intention through dialogue to find and solve problems, and finally, provides a response in text or animation.
The book is aimed at researchers and students interested in artificial intelligence, robotics, and cognitive science. Based on philosophical considerations, the methodology will also have an appeal in linguistics, psychology, ontology, geography, and cartography.
Key Features:
Describes the methodology to provide robots with human-like capability of natural language understanding (NLU) as the central part of IMU
Uses methodology that also relates to linguistics, psychology, ontology, geography, and cartography
Examines current trends in machine translation
Table of Contents
Table of Contents:
Introduction
Anna - an ideal home robot
Intuitive human-robot interaction
Integrative multimedia understanding and natural language understanding
Knowledge and cognition
Natural Language Processing Viewed from Semantics
Trends in machine translation
Case study of current MT systems (as of October, 2018)
Fundamentals for Robotic NLU
NLU in accordance with semiotics
Syntactic analysis
Semantic analysis and pragmatic analysis
Robust NLU
Response synthesis
Syntax and semantics of discourse
Cognitive Essentials for Midst
Functional model of human mind
Human knowledge and cognitive propensities
Semantics and mental image
QSIs (quasi-symbolic images) and human concept system
Primitive quasi-symbolic images
Perception of causality
Semantic articulation and QSI connectors
Negation of mental image
Imaginary space region
Computational Model of Mental Image
Atomic locus as primitive QSI
Temporal conjunctions as QSI connectors
Empty event
Attributes and Standards
Formal System
Semantic principle of Lmd
Syntax of Lmd
Tempo-logical connectives
Formulation of event concepts
Formulation of laws of the world
Fundamental Postulates and Inference Rules for Deductive System
Properties of Loci
Inference rules for deduction
Tempo-logical deduction with TLCs
Human-Specific Semantics of 4d Language as Mental Images
Conventional approaches to 4D language understanding
4D language semantics as mental images
Formulation of concepts of spatial prepositions
Properties of static 4D concepts as human intuitive mental images
Reversal operation on spatial change event concepts as mental images
Problem Finding and Solving in Formal System
Definition of problem and task
Creation problem finding and solving
Maintenance problem finding and solving
Human Language Understanding by Robots
Two-staged robotic NLU
Robotic concept system for iHRI
Compound concept system for robots
Robot manipulation as cross-media operation via Lmd
Aware computing in robots
Homogeneous/Inhomogeneous Communication
4d Language Understanding for Cognitive Robotics
Requirements for robotic NLU
Logical Adequacy of Lmd
Translation between NL and Lmd
Reasoning in Lmd
Anchoring via Lmd
Behavioralization via Lmd
Systematic interpretation of Lmd
Multilingual Operation Via Lmd
Meaning definition
Optimization of grammatical description for word meaning definition
Language operation via Lmd
Question answering through Lmd
Computational Model of Japanese for NLU
Brief description of basic Japanese
Phrase structure grammar for Japanese
Dependency grammar for Japanese
Sentence and discourse of Japanese
Sentence types of Japanese and phrasing
Implementation of Mental-Image Based Understanding
Configuration of CMS
MBU versus conventional NLU
Stimulus sentences to CMS and human subjects
Mental image based understanding by CMS
Problem finding and solving in CMS
Awareness control of CMS
Conclusions
References