From the reviews of the third edition: "This enlarged edition of Information and Self-Organization addresses the concept of information in depth: ranging 'from Shannon information, from which all semantics has been exorcised, to the effects of information on receivers and the self-creation of meaning'-that is, toward semantic information ... . Nevertheless, both the qualitative lessons and quantitative analysis presented in the book ... very useful for artificial life researchers." (Mikhail Prokopenko, Artificial Life, Vol. 15, 2009)

• The Challenge of Complex Systems.- From the Microscopic to the Macroscopic World ....- ... and Back Again: The Maximum Information Principle (MIP).- An Example from Physics: Thermodynamics.- Application of the Maximum Information Principle to Self-Organizing Systems.- The Maximum Information Principle for Nonequilibrium Phase Transitions: Determination of Order Parameters, Enslaved Modes, and Emerging Patterns.- Information, Information Gain, and Efficiency of Self-Organizing Systems Close to Their Instability Points.- Direct Determination of Lagrange Multipliers.- Unbiased Modeling of Stochastic Processes: How to Guess Path Integrals, Fokker-Planck Equations and Langevin-Îto Equations.- Application to Some Physical Systems.- Transitions Between Behavioral Patterns in Biology. An Example: Hand Movements.- Pattern Recognition. Unbiased Guesses of Processes: Explicit Determination of Lagrange Multipliers.- Information Compression in Cognition: The Interplay between Shannon and Semantic Information.- Quantum Systems.- Quantum Information.- Quantum Computation.- Concluding Remarks and Outlook.

From the reviews of the third edition: "This enlarged edition of Information and Self-Organization addresses the concept of information in depth: ranging 'from Shannon information, from which all semantics has been exorcised, to the effects of information on receivers and the self-creation of meaning'-that is, toward semantic information ... . Nevertheless, both the qualitative lessons and quantitative analysis presented in the book ... very useful for artificial life researchers." (Mikhail Prokopenko, Artificial Life, Vol. 15, 2009)

• The Challenge of Complex Systems.- From the Microscopic to the Macroscopic World ....- ... and Back Again: The Maximum Information Principle (MIP).- An Example from Physics: Thermodynamics.- Application of the Maximum Information Principle to Self-Organizing Systems.- The Maximum Information Principle for Nonequilibrium Phase Transitions: Determination of Order Parameters, Enslaved Modes, and Emerging Patterns.- Information, Information Gain, and Efficiency of Self-Organizing Systems Close to Their Instability Points.- Direct Determination of Lagrange Multipliers.- Unbiased Modeling of Stochastic Processes: How to Guess Path Integrals, Fokker-Planck Equations and Langevin-Îto Equations.- Application to Some Physical Systems.- Transitions Between Behavioral Patterns in Biology. An Example: Hand Movements.- Pattern Recognition. Unbiased Guesses of Processes: Explicit Determination of Lagrange Multipliers.- Information Compression in Cognition: The Interplay between Shannon and Semantic Information.- Quantum Systems.- Quantum Information.- Quantum Computation.- Concluding Remarks and Outlook.

From the reviews of the third edition: "This enlarged edition of Information and Self-Organization addresses the concept of information in depth: ranging 'from Shannon information, from which all semantics has been exorcised, to the effects of information on receivers and the self-creation of meaning'-that is, toward semantic information ... . Nevertheless, both the qualitative lessons and quantitative analysis presented in the book ... very useful for artificial life researchers." (Mikhail Prokopenko, Artificial Life, Vol. 15, 2009)

• The Challenge of Complex Systems.- From the Microscopic to the Macroscopic World ....- ... and Back Again: The Maximum Information Principle (MIP).- An Example from Physics: Thermodynamics.- Application of the Maximum Information Principle to Self-Organizing Systems.- The Maximum Information Principle for Nonequilibrium Phase Transitions: Determination of Order Parameters, Enslaved Modes, and Emerging Patterns.- Information, Information Gain, and Efficiency of Self-Organizing Systems Close to Their Instability Points.- Direct Determination of Lagrange Multipliers.- Unbiased Modeling of Stochastic Processes: How to Guess Path Integrals, Fokker-Planck Equations and Langevin-Îto Equations.- Application to Some Physical Systems.- Transitions Between Behavioral Patterns in Biology. An Example: Hand Movements.- Pattern Recognition. Unbiased Guesses of Processes: Explicit Determination of Lagrange Multipliers.- Information Compression in Cognition: The Interplay between Shannon and Semantic Information.- Quantum Systems.- Quantum Information.- Quantum Computation.- Concluding Remarks and Outlook.