With an Introduction and Notes by Hugh Epstein, Secretary of the Joseph Conrad Society of Great Britain 'Then the vision of an enormous town prented itself, of a monstrous town...a cruel devourer of the world's light. There was room enough there to place any story, depth enough for any passion, variety enough there for any setting, darkness enough to bury five millions of lives.' Conrad's 'monstrous town' is London, and his story of espionage and counter-espionage, anarchists and embassies, is a detective story that becomes the story of Winnie Verloc's tenacity in maintaining her devotion to her peculiar and simple-minded brother, Stevie, as they pursue their very ordinary lives above a rather dubious shop in the back streets of Soho. AUTHOR: Born Jozef Teodor Konrad Nalecz Korzeniowski in Poland in 1857, Conrad served in the British Merchant Service (1878-94), travelling to Africa, Australia, India, Indonesia and the Orient, becoming a British citizen in 1886. Turning to full-time writing in 1894, his years at sea featured heavily in his early works. His novels, such as 'Lord Jim', and his novella 'Heart of Darkness' (on which the film 'Apocalypse Now' was based) have brought him an enduring reputation.
Striking full-color guides. Bound in water repellent, film laminated covers. Extensive center-spread maps of the state highlights locations featured in each book. Special 8-pocket and 4-pocket lucite display racks available with purchase of the series.
This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference.