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In many companies, two or three executives jointly hold the responsibilities at the top-from the charismatic CEO who relies on the operational expertise of a COO, to co-CEOs who trust in inter-personal bonds to achieve professional results. Their collaboration is essential if they are to address the dilemmas of the top job and the demands of today's corporate governance. Sharing Executive Power examines the behaviour of such duos, trios and small teams, what roles their members play and how their professional and inter-personal relationships bind their work together. It answers some critical questions regarding when and how such power sharing units form and break up, how they perform and why they endure. Understanding their dynamics helps improve the design and composition of corporate power structures. The book is essential reading for academics, graduates, MBAs, and executives interested in enhancing teamwork and cooperation at the top.

Corporate governance. --- Chief executive officers. --- Directors of corporations. --- Decision making --- Leadership. --- Decision making. --- Ability --- Command of troops --- Followership --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Corporate directors --- Corporation directors --- Corporations --- Corporate governance --- CEOs (Executives) --- Executive officers, Chief --- Executives --- Governance, Corporate --- Industrial management --- Directors of corporations --- Business, Economy and Management --- Business Management

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Complex analysis --- Mathematical statistics --- Evolution. Phylogeny --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- beeldverwerking --- factoranalyse --- complexe analyse (wiskunde) --- informatica --- Europees recht --- KI (kunstmatige intelligentie) --- robots

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The computational paradigm considered here is a conceptual, theoretical and formal framework situated above machines and living creatures (two instant- tions), su?ciently solid, and still non-exclusive, that allows us: 1. tohelpneuroscientiststoformulateintentions,questions,experiments,me- ods and explanation mechanisms assuming that neural circuits are the p- chological support of calculus; 2. to help scientists and engineers from the ?elds of arti?cial intelligence (AI) and knowledge engineering (KE) to model, formalize and program the c- putable part of human knowledge; 3. to establish an interaction framework between natural system computation (NSC) and arti?cial system computation (ASC) in both directions, from ASC to NSC (in computational neuroscience), and from NSC to ASC (in bioinspired computation). With these global purposes, we organized IWINAC 2005, the 1st International Work Conference on the Interplay Between Natural and Arti?cial Computation, whichtookplaceinLasPalmasdeGranCanaria,CanaryIslands(Spain),during June 15-18, 2005, trying to contribute to both directions of the interplay: I: From Arti?cial to Natural Computation. What can computation, arti?cial intelligence (AI) and knowledge engineering (KE) contribute to the und- standing of the nervous system, cognitive processes and social behavior? This is the scope of computational neuroscience and cognition, which uses the computational paradigm to model and improve our understanding of natural science.

Computers. --- Algorithms. --- Artificial intelligence. --- Optical data processing. --- Pattern recognition. --- Evolutionary biology. --- Computation by Abstract Devices. --- Algorithm Analysis and Problem Complexity. --- Artificial Intelligence. --- Image Processing and Computer Vision. --- Pattern Recognition. --- Evolutionary Biology.

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Computer science. --- Algorithms. --- Artificial intelligence. --- Computer vision. --- Pattern recognition systems. --- Evolution (Biology). --- Theory of Computation. --- Algorithms. --- Artificial Intelligence. --- Computer Vision. --- Automated Pattern Recognition. --- Evolutionary Biology.

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Computer science. --- Algorithms. --- Artificial intelligence. --- Computer vision. --- Pattern recognition systems. --- Evolution (Biology). --- Theory of Computation. --- Artificial Intelligence. --- Computer Vision. --- Automated Pattern Recognition. --- Evolutionary Biology.