Linked e-resources
Details
Table of Contents
Preface; Cognitive Perspectives; Computational Perspectives; Natural Sciences Perspectives; Philosophical Perspectives; Logical Perspectives; Machine Perspectives; Contents; Contributors; Cognitive Perspectives; 1 Information and Reference; Abstract; 1 Introduction; 2 Background; 3 Physicality of Aboutness; 4 Steps to a Formalization of Reference; 5 Active Acquisition of Information; 6 Conclusion; References; 2 Modelling Empty Representations: The Case of Computational Models of Hallucination; Abstract; 1 Introduction; 2 Charles Bonnet Syndrome and Representations.
3 Computational Modelling of Hallucination4 Representational Mechanisms and Hallucinations; 5 Conclusion; Acknowledgements; References; 3 Life is Precious Because it is Precarious: Individuality, Mortality and the Problem of Meaning; Abstract; 1 Introduction; 2 The Problem of Meaning; 3 The Problem of Individuality; 4 The Problem of Mortality; 5 The Role of Death in Traditional Worldviews; 6 The Role of Death in Enactive Cognitive Science; 7 On the Impossibility of a Virtual Death; 8 Conclusions; Acknowledgements; References.
4 Language Processing, Computational Representational Theory of Mind and Embodiment: Inferences on VerbsAbstract; 1 Introduction; 2 Automatic Processing; 3 The Assumption in Cognitive Linguistics Regarding Verb Taxonomy May Be in Error; 4 Self-organizing Maps; 5 Pragmatics and Emotional Inferences; 6 Discussion; References; Computational Perspectives; Knowledge, Representation and the Dynamics of Computation; 1 Introduction; 2 Metaspaces; 2.1 General; 2.2 Action Spaces; 2.3 Knowledge Spaces; 3 Computation; 3.1 Relevant Spaces; 3.2 Defining Computation; 4 Dynamics; 4.1 Composing Computations.
4.2 Reflections5 Exploring Knowledge Spaces by Computation; 5.1 Knowledge Generation; 5.2 Knowledge Recognition; 6 Conclusion; References; Abstraction and Representation in Living Organisms: When Does a Biological System Compute?; 1 Introduction; 2 The Framework; 2.1 Formalising Representation; 2.2 Theory and Experiment; 2.3 Engineering; 2.4 Computation; 2.5 Encoding and Representation; 2.6 Signalling; 2.7 Arbitrariness of Encoding; 3 Intrinsic Representation; 3.1 Representational Entities; 3.2 Signatures of Representation; 4 Representation in Biological Systems; 4.1 Bacteria; 4.2 DNA.
4.3 Photosynthesis5 Summary and Conclusions; References; The Information-Theoretic and Algorithmic Approach to Human, Animal, and Artificial Cognition; 1 The Algorithmic Model of Mind; 1.1 The Turing Test Is Trivial, Ergo the Mind Is Algorithmic; 2 Algorithmic Complexity as Model of the Mind; 2.1 From Bias to Bayes; 2.2 The Coding Theorem Method; 2.3 The Block Decomposition Method; 3 Cognition and Complexity; 3.1 Working Memory; 3.2 Randomness Perception; 3.3 Culture and Structure; 4 Concluding Remarks; References.
3 Computational Modelling of Hallucination4 Representational Mechanisms and Hallucinations; 5 Conclusion; Acknowledgements; References; 3 Life is Precious Because it is Precarious: Individuality, Mortality and the Problem of Meaning; Abstract; 1 Introduction; 2 The Problem of Meaning; 3 The Problem of Individuality; 4 The Problem of Mortality; 5 The Role of Death in Traditional Worldviews; 6 The Role of Death in Enactive Cognitive Science; 7 On the Impossibility of a Virtual Death; 8 Conclusions; Acknowledgements; References.
4 Language Processing, Computational Representational Theory of Mind and Embodiment: Inferences on VerbsAbstract; 1 Introduction; 2 Automatic Processing; 3 The Assumption in Cognitive Linguistics Regarding Verb Taxonomy May Be in Error; 4 Self-organizing Maps; 5 Pragmatics and Emotional Inferences; 6 Discussion; References; Computational Perspectives; Knowledge, Representation and the Dynamics of Computation; 1 Introduction; 2 Metaspaces; 2.1 General; 2.2 Action Spaces; 2.3 Knowledge Spaces; 3 Computation; 3.1 Relevant Spaces; 3.2 Defining Computation; 4 Dynamics; 4.1 Composing Computations.
4.2 Reflections5 Exploring Knowledge Spaces by Computation; 5.1 Knowledge Generation; 5.2 Knowledge Recognition; 6 Conclusion; References; Abstraction and Representation in Living Organisms: When Does a Biological System Compute?; 1 Introduction; 2 The Framework; 2.1 Formalising Representation; 2.2 Theory and Experiment; 2.3 Engineering; 2.4 Computation; 2.5 Encoding and Representation; 2.6 Signalling; 2.7 Arbitrariness of Encoding; 3 Intrinsic Representation; 3.1 Representational Entities; 3.2 Signatures of Representation; 4 Representation in Biological Systems; 4.1 Bacteria; 4.2 DNA.
4.3 Photosynthesis5 Summary and Conclusions; References; The Information-Theoretic and Algorithmic Approach to Human, Animal, and Artificial Cognition; 1 The Algorithmic Model of Mind; 1.1 The Turing Test Is Trivial, Ergo the Mind Is Algorithmic; 2 Algorithmic Complexity as Model of the Mind; 2.1 From Bias to Bayes; 2.2 The Coding Theorem Method; 2.3 The Block Decomposition Method; 3 Cognition and Complexity; 3.1 Working Memory; 3.2 Randomness Perception; 3.3 Culture and Structure; 4 Concluding Remarks; References.