本书通过考察最新的关于AI与哲学关系的无关论、等同论和接管论等，探究哲学在AI基础理论建设、技术建构、框架和未来学问题之解决中的具体作用，对哲学与AI的关系作新的探讨；对AI在意向性、语义性、自主体、本体论、知识工程、创造力等基础问题上的研究历史、现状及存在的问题做出考察，着力揭示建模这类智能现象所依据的基础理论中渗透着民间心理学的“小人理论”这一事实，进而为AI建模和机器实现的方向选择和战略发展提供可能的建议。本书的创新和突出特点表现在：针对AI缺乏对创造力的建模，特别是我国对计算创造力这一AI分支所知甚少的情况，本书用了一定篇幅来探讨计算创造力的来龙去脉、最新发展、主要成就，对其存在的问题从哲学上作了思考和诊断，对在我国AI领域的发展路径进行了初步探索与思考。

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1978-1982,华中师范大学政教系学习政治教育 1982-1984，武汉大学哲学系，随陈修斋杨祖陶攻读外国哲学硕士学位 1984一至今，在华中师范大学从事哲学教学和研究工作1984年至今，在华中师范大学从事哲学教学和研究工作承担国家社科基金和教育部项目10多项，出版学术专著13部、译著6部，约1000万字的科研成果。

目录
前言/001
上篇 常思常新的AI与哲学的关系问题
第一章 相关概念辨析及AI与哲学关系问题争论概说
第一节 计算哲学、AI的哲学和哲学的AI/003
第二节 “AI即哲学”的争论与接管论/005
第三节 “哲学需要AI就像AI需要哲学”与通用认知架构/010
第四节 AI的定义问题与“可怜的科学家- 可怜的哲学家”/013
第二章 AI基础理论建设中的哲学
第一节 AI基础理论建设中的哲学逻辑的身影/019
第二节 “AI中的哲学与理论”/023
第三节 从AI专家的智能观建构看哲学在AI中的作用/030
第四节 《剑桥AI手册》和有关教科书论哲学在AI基础理论建设中的作用/036
第五节 哲学家对AI基础理论建设的哲学思考/046
第三章 从AI的技术建构工作看哲学对AI的作用
第一节 AI的自主体研究及其哲学基础/060
第二节 表征与本体论/068
第三节 不完全性定理与AI对哲学的依赖性/074
第四节 AI在科学- 前科学系谱中的地位问题/076
第五节 机器学习与心理测量学的AI/081
第四章 从框架问题研究看哲学在AI中的作用
第一节 框架问题的重要性、不同理解与精神实质/089
第二节 框架问题的AI和哲学掘进/100
第三节 “操作性形而上学”与框架问题的进一步探原及哲学在其解决中的作用/109
第五章 从AI的未来学研究看哲学对AI的意义
第一节 超级智能及其哲学问题/116
第二节 进化、加速回报定律与“灵性机时代”/125
第三节 智能奇点、智能大爆炸与“后奇点”世界中的人类/135
第四节 从奇点悖论、超级智能的争论看哲学对AI的意义/151
第六章 AI对哲学的意义与两者互利互惠关系的内在机制
第一节 哲学是计算革命的最大受益者/158
第二节 哲学与AI的复杂关系及其认知条件/166
第三节 哲学是AI的一个支柱及其内在机制/170
中篇 智能观、工程本体论、意向性与自主体建模问题
第七章 “图灵测试”新解、自然智能与智能观的相关问题
第一节 “图灵测试”及其智能观：新解、批评与新的形态/178
第二节 计算主义对图灵问题的化解与对新智能观的阐发/197
第三节 “中文屋论证”及其引发的智能观论战/199
第四节 复杂性视域下的智能“多—一”“同—异”问题/206
第五节 自然计算与智能观的进一步思考/212
第八章 工程本体论：AI对人的本体论构架的解析与建构
第一节 本体论的多元化发展与工程本体论的诞生/237
第二节 AI本体论的缘起、结构与本质特点/243
第三节 AI本体论个例考释/246
第四节 本体论多元发展的必然性与意义/250
第九章 新计算主义与意向性建模的祛魅及尝试
第一节 经典计算主义的问题与新计算主义的兴起/254
第二节 计算概念的重新阐释/256
第三节 智能具有意向性的机制与AI对意向性的建模/260
第四节 计算主义的“宽”与“窄”/264
第十章 意向性“建筑术”及其对AI瓶颈问题的进一步消解
第一节 麦金论人类意向性的结构、运作机理与实质/270
第二节 问题诊断与“生物学转向”/274
第三节 模型方法与心灵建筑术/276
第十一章 关于意向性的BDI 模型与AI建模的方向问题
第一节 基本概念分析与人类心智解剖/284
第二节 概念框架与关于意向性的BDI 模型/291
第三节 AI建模的基础：是民间心理学还是发展着的心灵哲学？/293
第四节 AI建模的若干心灵哲学思考/298
第十二章 自主体解析、建模及其哲学问题
第一节 自主体在古今哲学中的遭遇/307
第二节 AI的自然自主体解剖与理论建模/324
第三节 典型的自主体形式及其理论基础/329
第四节 关于自主体建模基础的思考/337
第十三章 面对AI基础理论难题的联结主义及其创新发展
第一节 联结主义及其计算主义实质/341
第二节 联结主义的AI哲学探讨与争论/344
第三节 联结主义面临的“意向性缺失难题”及其化解/347
第四节 基于反馈型神经网络和人工感知机的分析/353
第五节 面对难题的创新尝试：基于进化新解的人脑逆向工程/357
第六节 面对难题的创新发展尝试：“类人脑AI”与“新AI”/360
第十四章 自然语言机器处理中的语义性问题及其化解
第一节 自然语言机器处理研究的一般进程与语义性缺失问题/378
第二节 本体论语义学对语义缺失根源的探讨/385
第三节 机器实现语义加工的尝试性探讨/389
第四节 意义与启示/392
下篇 计算创造力与人工智能的“实至名归”
第十五章 作为AI终极前沿的计算创造力的崛起与意义
第一节 计算创造力的兴起与概念化/400
第二节 计算创造力的理解与相关基本问题/415
第三节 计算创造力研究的意义及其与AI的关系/431
第十六章 计算创造力的前提性问题及其哲学审视
第一节 创新观祛魅与重构：AI创造力建模的首要前提/437
第二节 怀疑论挑战与创造力机器建模的可能性问题/446
第三节 创造力的计算化说明与通向机器实现之“隧道”的打通/454
第四节 原型实例：创造力计算建模的范例问题/475
第十七章 计算创造力的“怎么都行”的方法论
第一节 计算主义的坚持和发展/483
第二节 非人类中心主义的方法论/494
第三节 语料库语言学方法、统计方法及其与工程本体论的融合/504
第四节 计算创造力的突现论方案/513
第五节 情境主义方法论/526
第六节 基于解释的学习—计算创造力方案/540
第七节 计算创造力的“过程—成果”方案及其他/546
第十八章 AI的创造力建模尝试与典型模型考察
第一节 创造力的形式化理论及其模型/564
第二节 创新系统框架及其发展/576
第三节 创造力的单一过程、方面和机制的建模/588
第四节 创新系统的放大与创造力建模的延展性方案/634
第十九章 计算创造力的焦点- 热点问题与重大课题
第一节 怀疑论问题的进一步思考/682
第二节 作为计算创造力研究的“牛鼻子”的软件工程/696
第三节 活算法：计算创造力从理想到现实的枢纽/707
第四节 计算创造力的框架、机制与领域通用性- 专门性问题/719
第五节 计算创造力研究中的美学、自我学、伦理学问题及其他/733
第二十章 创造力支持工具、协同创造力与群体创造力
第一节 创造力支持工具/756
第二节 人机协同创新/765
第三节 共创造力与群体创造力/775
第二十一章 文学艺术创造力的工程学建模实践
第一节 文学艺术创造力建模与机器实现的一般问题与进程/804
第二节 音乐创造力机器建模与音乐作品生成系统/806
第三节 绘画创造力的机器实现/820
第四节 综合性艺术创造力的计算实现/827
第五节 文学创作软件的开发与故事生成系统/831
第二十二章 科学创造力的计算建模与机器实现
第一节 科学创造力计算实现研究的一般进程和基本理论问题/856
第二节 人类专家无法匹敌的预测DNA 和RNA 结构的软件工程/864
第三节 类比推理与卢瑟福科学发现过程的重演/868
第四节 科学定律的图解表征与HUYGENS 系统/874
第五节 科学发现的计算程序与能完成定量经验发现的BACON/877
第六节 创造力机器实现的形式探索与概念创新系统/884
第二十三章 其他形式创造力的计算建模与机器实现
第一节 刑侦创造力与“犯罪计算意外发现系统”/901
第二节 决策中的计算创造力系统/906
第三节 “计算游戏创造力”的理论研究与机器实现尝试/909
第四节 语言创造力的计算建模与机器实现/921
第五节 其他形式创造力的计算建模与机器实现尝试/933
第二十四章 计算创造力的评价问题研究
第一节 计算创造力评价研究的缘起、基本问题与主要走向/942
第二节 计算创造力的本体论地位问题与“事后评价”论/946
第三节 计算创造力评价的内在性、创造力三脚架与图解式形式体系/949
第四节 “不公平”问题与“新手构架”/959
第五节 “经验基础”问题、价值问题与基于交互设计的价值论评估方案/966
第六节 “系统思维”框架下的创新、评价与责任及其问题/985
第七节 计算创造力的元评价问题/987
第八节 创新阶段的谱系问题与过滤评价系统的建构/992
第九节 专门领域的计算创造力的评价问题/995
结语 人工智能、计算创造力与哲学创造力研究的
若干问题/1013
参考文献/1034
索引/1087
后记/1099
PREFACE/001
PART I THE EVER-RENEWING RELATIONSHIP BETWEEN AI AND PHILOSOPHY
CHAPTER 1 CONCEPTS CLARIFICATION AND AN OVERVIEW OF THE PHILOSOPHY- AIRELATIONSHIP DEBATE
1.1 Computational Philosophy, the Philosophy of AI, and Philosophical AI/003
1.2 The Debate on “AIis Philosophy” and the “Takeover Theory”/005
1.3 “Philosophy Needs AIas much as AINeeds Philosophy”and General Cognitive Architecture/010
1.4 The Definition of AIand “The Poor Scientist - The Poor Philosopher”/013
CHAPTER 2 PHILOSOPHY IN THE CONSTRUCTION OF AI’S FOUNDATIONAL THEORIES
2.1 The Presence of Philosophical Logic in the Construction of AI’s Foundational Theories/019
2.2 “Philosophy and Theory in AI”/023
2.3 Philosophical Contributions to AIfrom Experts’ Construction of Intelligent Views/030
2.4 The Cambridge Handbook of Artificial Intelligence and Relevant Textbooks on the Role of Philosophy in the Construction of AI’s Foundational Theories/036
2.5 Philosophers’ Philosophical Reflections on the Construction of AI’s Foundational Theories/046
CHAPTER 3 THE ROLE OF PHILOSOPHY IN AIFROM THE PERSPECTIVE OF TECHNICAL CONSTRUCTION
3.1 The Study of AIAgents and Its Philosophical Foundations/060
3.2 Representation and Ontology/068
3.3 The Incompleteness Theorem and AI’s Dependence on Philosophy/074
3.4 The Status of AIin the Science-Pre-Science Genealogy/076
3.5 Machine Learning and AIin Psychometric Assessment/081
CHAPTER 4 THE ROLE OF PHILOSOPHY IN AIFROM THE STUDY OF THE FRAME PROBLEM
4.1 The Importance, Diverse Interpretations, and Essence of the Frame Problem/089
4.2 The Philosophical and AIExploration of the Frame Problem/100
4.3 “Operative Metaphysics” and Further Exploration of the Frame Problem and the Role of Philosophy in Its Solution/109
CHAPTER 5 THE SIGNIFICANCE OF PHILOSOPHY TO AIFROM THE STUDY OF AIFUTUROLOGY
5.1 Superintelligence and Its Philosophical Issues/116
5.2 Evolution, the Law of Accelerating Returns, and “the Age of Spiritual Machines”/125
5.3 The Intelligent Singularity, the Intelligence Explosion, and Humanity in the“Post-Singularity” World/135
5.4 The Significance of Philosophy for AIfrom the Paradox of the Singularity and the Debate on Superintelligence/151
CHAPTER 6 AI’S IMPACT ON PHILOSOPHY AND THE INTRINSIC MECHANISMS OF THEIR SYMBIOTIC RELATIONSHIP
6.1 Philosophy as the Greatest Beneficiary of the Computational Revolution/158
6.2 The Complex Relationship Between Philosophy and AIand Its Cognitive Conditions/166
6.3 Philosophy as a Pillar of AIand Its Intrinsic Mechanism/170
PART II INTELLIGENT VIEWS, ENGINEERING ONTOLOGY,INTENTIONALITY, AND AGENT-BASED MODELING
CHAPTER 7 NEW INTERPRETATIONS OF THE “TURING TEST”,NATURAL INTELLIGENCE, AND ISSUES RELATED TO INTELLIGENT VIEWS
7.1 The “Turing Test” and Its Intelligent View: New Interpretations, Criticisms,and Emerging Paradigms/178
7.2 Computationalism’s Resolution of the Turing Problem and the Elucidation of a New Intelligent View/197
7.3 The “Chinese Room Argument” and the Resulting Debate on Intelligent Views/199
7.4 The “Many-One” and “Similarity-Difference” Issues in Intelligence from a Complexity Perspective/206
7.5 Further Reflections on Natural Computing and Intelligent Views/212
CHAPTER 8 ENGINEERING ONTOLOGIES: AI’S ANALYSIS AND CONSTRUCTION OF HUMAN ONTOLOGICAL FRAMEWORK
8.1 The Diversified Development of Ontologies and the Birth of Engineering Ontologies/237
8.2 The Origin, Structure, and Characteristics of AIOntology/243
8.3 Case Studies and Critical Analysis of AIOntology/246
8.4 The Necessity and Implications of the Pluralistic Development of Ontology/250
CHAPTER 9 NEW COMPUTATIONALISM AND THE DEMYSTIFICATION AND ATTEMPTS OF MODELING INTENTIONALITY
9.1 The Problems of Classical Computationalism and the Rise of New Computationalism/254
9.2 The Reinterpretation of the Concept of Computation/256
9.3 The Mechanism that Intelligence Has Intentionality and the Modeling of Intentionality by AI/260
9.4 The “Wide” vs. “Narrow” in Computationalism/264
CHAPTER 10 THE “ARCHITECTURE OF INTENTIONALITY” AND ITS RESOLUTION OF BOTTLENECK ISSUES IN AI
10.1 McGinn’s Discussion on the Structure, Operative Mechanism, and Nature of Human Intentionality/270
10.2 Problem Diagnosis and the “Biological Turn”/274
10.3 The Models Method and the Architecture of the Mind/276
CHAPTER 11 THE “BDI MODEL” OF INTENTIONALITY AND THE DIRECTION OF AIMODELING
11.1 Analysis of Basic Concepts and the Anatomy of the Human Mind/284
11.2 Conceptual Framework and the BDI Model of Intentionality/291
11.3 The Foundation of AIModeling: Folk Psychology or Evolving Philosophy of Mind?/293
11.4 Reflections on AIModeling from the Perspective of Philosophy of the Mind/298
CHAPTER 12 ANALYSIS AND MODELING OF AGENTS AND ITS PHILOSOPHICAL PROBLEMS
12.1 The Concept of Agents in Ancient and Modern Philosophy/307
12.2 Analysis and Theoretical Modeling of Natural AIAgents/324
12.3 Typical Forms of Agents and Their Theoretical Foundations/329
12.4 Reflections on the Foundation of Agent Modeling/337
CHAPTER 13 CONNECTIONISM IN THE FACE OF AI’S FOUNDATIONAL THEORETICAL CHALLENGES AND ITS INNOVATIVE DEVELOPMENT
13.1 Connectionism and Its Computationalist Essence/341
13.2 Connectionist Discussion and Debates on AI/344
13.3 The Problem of Absence of Intentionality in Connectionism and Its Resolution/347
13.4 Analysis Based on Feedback Neural Networks and Artificial Perceptrons/353
13.5 Innovative Attempts in the Face of Challenges: Reverse-Engineering the Brain Based on Evolutionary Interpretations/357
13.6 Innovative Attempts in the Face of Challenges: “Human-Like AI” and“New AI”/360
CHAPTER 14 THE SEMANTICS OF NATURAL LANGUAGE PROCESSING AND ITS RESOLUTION
14.1 How Natural Language Processing Works and Semantic Deficits in it/378
14.2 Discussions on the Causes of Semantic Deficits in Ontological Semantics/385
14.3 Preliminary Exploration of Machine Semantic Processing/389
14.4 Significance and Implications/392
PART III COMPUTATIONAL CREATIVITY AND “APTLY NAMED”ARTIFICIAL INTELLIGENCE
CHAPTER 15 THE RISE AND IMPLICATIONS OF COMPUTATIONAL CREATIVITY AS THE ULTIMATE FRONTIER OF AI
15.1 The Emergence and Conceptualization of Computational Creativity/400
15.2 Understanding Computational Creativity and the Basics/415
15.3 The Significance of Computational Creativity Research and Its Connection to AI/431
CHAPTER 16 PRELIMINARY QUESTIONS OF COMPUTATIONAL CREATIVITY AND ITS PHILOSOPHICAL EXAMINATION
16.1 Demystification and Reconstruction of the View of Creativity: The Primary Premise for AIModeling for Creativity/437
16.2 Challenges from the Skeptics and the Possibility of Creativity Modeling/446
16.3 Computational Explanations of Creativity and Pathways to Machine Realization/454
16.4 Prototype Instances: Paradigm Problems in Creative Computational Modeling/475
CHAPTER 17 AN “ANYTHING GOES” METHODOLOGY OF COMPUTATIONAL CREATIVITY
17.1 The Persistence and Development of Computationalism/483
17.2 The Methodology of Non-Anthropocentrism/494
17.3 Integration of Corpus Linguistics, Statistical Methods, and Engineering Ontologies/504
17.4 Emergentist Approaches to Computational Creativity/513
17.5 Situationist Methodologies/526
17.6 Explanation-Based Learning-Computational Creativity Scheme/540
17.7 The “Process-Outcome” Scheme of Computational Creativity and Others/546
CHAPTER 18 CREATIVITY MODELING ATTEMPT AND TYPICAL MODEL INVESTIGATION IN AI
18.1 Formal Theories of Creativity and Their Models/564
18.2 The Framework of Creativity Systems and Their Development/576
18.3 Modeling of Singular Process, Aspects, and Mechanism of Creativity/588
18.4 Schemes for Creativity Systems Amplification and Creativity Modeling Extension/634
CHAPTER 19 KEY ISSUES AND MAJOR TOPICS IN COMPUTATIONAL CREATIVITY
19.1 Further Reflections on Skeptical Issues/682
19.2 Software Engineering as the Key to Computational Creativity Research/696
19.3 Living Algorithms: The Hub from Ideal to Reality in Computational Creativity/707
19.4 Framework, Mechanisms, and Domain-General or Domain-Specific Issues in Computational Creativity/719
19.5 Aesthetics, Selfology, Ethics, and Other Issues in Computational Creativity Research/733
CHAPTER 20 CREATIVITY SUPPORT TOOLS, COLLABORATIVE CREATIVITY, AND GROUP CREATIVITY
20.1 Creativity Support Tools/756
20.2 Human-Machine Collaborative Creativity/765
20.3 Co-Creativity and Group Creativity/775
CHAPTER 21 ENGINEERING MODELING PRACTICES OF LITERARY AND ARTISTIC CREATIVITY
21.1 General Issues and Process in the Modeling and Machine Realization of Literary and Artistic Creativity/804
21.2 Machine Modeling of Musical Creativity and Music Composition Generative Systems/806
21.3 Machine Realization of Painting Creativity/820
21.4 Computational Realization of Integrated Artistic Creativity/827
21.5 Development of Literary Creation Software and Story Generation Systems/831
CHAPTER 22 COMPUTATIONAL MODELING AND MACHINE REALIZATION OF SCIENTIFIC CREATIVITY
22.1 The General Process and Basic Theoretical Issues in the Computational Realization of Scientific Creativity/856
22.2 Software Engineering that Surpasses Human Experts in Predicting DNA and RNA Structures/864
22.3 Analogical Reasoning and the Reenactment of Rutherford’s Scientific Discovery Process/868
22.4 Pictorial Representation of Scientific Laws and the HUYGENS System/874
22.5 Computational Programs for Scientific Discovery and BACON for Quantitative Empirical Discovery/877
22.6 Formal Exploration and Conceptual Innovation Systems for the Machine Realization of Creativity/884
CHAPTER 23 COMPUTATIONAL MODELING AND MACHINE REALIZATION OF OTHER FORMS OF CREATIVITY
23.1 The Creativity of Criminal Investigation and “Crime Computing Accidental Discovery System”/901
23.2 Computational Creativity Systems in Decision-Making/906
23.3 Theoretical Research and Machine Realization of “Video Game Creativity”/909
23.4 Computational Modeling and Machine Realization of Language Creativity/921
23.5 Computational Modeling and Machine Realization of Other Forms of Creativity/933
CHAPTER 24 RESEARCH ON THE EVALUATION OF COMPUTATIONAL CREATIVITY
24.1 The Origin, Basic Issues, and Main Trends of Research on the Evaluation of Computational Creativity/942
24.2 The Ontological Status of Computational Creativity and the “Post Hoc Evaluation” Theory/946
24.3 The Intrinsic Nature of Computational Creativity Evaluation, the“Creativity Tripod”, and Pictorial Formal Systems/949
24.4 The “Unfairness” Issue and the “Novice Framework”/959
24.5 The “Empirical Basis”, Value, and Interaction-Based Value Assessment Schemes/966
24.6 Innovation, Evaluation, and Responsibility in the “Systems Thinking”Framework and Their Problems/985
24.7 The Meta-Evaluation of Computational Creativity/987
24.8 The Genealogy of Innovation Stages and the Construction of Filtering Evaluation Systems/992
24.9 Evaluation of Computational Creativity in Specialized Fields/995
CONCLUSION: SEVERAL ISSUES IN THE RESEARCH OF ARTIFICIAL INTELLIGENCE, COMPUTATIONAL CREATIVITY, AND PHILOSOPHICAL CREATIVITY/1013
BIBLIOGRAPHY/1034
INDEX/1087
POSTSCRIPT/1099