Preface -- Acknowledgements -- Contents -- Chapter 1 Introduction -- 1.1. Emergent computation as a universal phenomena -- 1.2. Emergence -- 1.3. Cellular computing systems -- 1.4. Universality -- 1.5. Designing for emergence, the essence of this book -- 1.6. Detecting the potential for emergence: the local activity theory -- Chapter 2 Cellular Paradigms -- 2.1. Cellular systems -- 2.2. Major cellular systems paradigms -- 2.3. Matlab simulation of generalized cellular automata -- 2.4. Simulation of Reaction-Diffusion Cellular Neural Networks -- 2.5. ConcIuding remarks -- Chapter 3 Universal Cells -- 3.1. Universality and cellular computation, basic ideas -- 3.2. Binary cells -- 3.2.1. What would be an "ideal" binary CNN cell ? -- 3.2.2. Orientations and Projection Tapes -- 3.2.3. Universal cells with canonical discriminants -- 3.2.4. Compact universal cells with multi nested discriminants -- 3.3. Continuous state cells -- 3.3.1. Overview -- 3.3.2. Some theoretical issues on simplicial neural cells -- 3.3.3. Circuit implementation issues -- 3.3.4. A general procedure for training the simplicial cell -- 3.3.5. Functional capabilities and applications -- 3.3.6. Nonlinear expansion of the input space -- 3.3.7 Comparison with multi-layer perceptrons -- 3.4. Concluding remarks -- Chapter 4 Emergence in Continuous-Time Systems -- 4.1. The theory of local activity as a tool for locating emergent behaviors -- 4.2. Narrowing the search, "Edge of chaos" domains -- 4.3. The methodology of finding "edge of chaos" domains -- 4.3.1. Four steps precluding the local activity testing -- 4.3.2. The concept of local activity -- 4.3.3. Testing for stable and unstable local activity -- 4.3.4. Unrestricted versus restricted local activity, the edge of chaos -- 4.3.5. Bifurcation diagrams -- 4.3.6. Emergent behaviors near and within the "edge of chaos".

4.4. Emergent behaviors within the "edge of chaos" domains of the Brusselator CNN -- 4.4.1. Local Activity and Edge of Chaos Domains -- 4.4.2. Emergence at the edge of chaos -- 4.5. Emergent behaviors within the "edge of chaos" domains of the Gierer-Meinhardt CNN -- 4.5.1. Local Activity and Edge of Chaos Domains -- 4.5.2. Emergence at the edge of chaos -- 4.6. Concluding remarks and engineering perspectives -- Chapter 5 Emergence in Discrete-Time Systems -- 5.1 Emergent phenomena in binary cellular automata -- 5.1.1. Introduction -- 5.1.2. Generalized Cellular Automata -- 5.1.3. Failure boundaries and paving stones in the cell's parameter space -- 5.1.4. Locating emergent behaviors and their dynamics -- 5.2. Emergent phenomena in continuous state cellular automata -- 5.1.1. Introduction -- 5.2.1. The cellular model -- 5.2.2. Emergence of autopoietic patterns by mutations in the "game of life" -- 5.3. Emergence in coupled generalized cellular automata -- 5.3.1 Introduction -- 5.3.2. The cellular model -- 5.3.3. An application in pattern detection from extremely noisy background -- 5.4. Concluding remarks -- Chapter 6 Unconventional Applications -- 6.1. Introduction -- 6.2. Generating the stimuli -- 6.3. Experimental results -- 6.4. Concluding remarks -- References -- Index -- About the Author.