{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T13:36:02Z","timestamp":1648647362173},"reference-count":42,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. Game Theory Rev."],"published-print":{"date-parts":[[2005,9]]},"abstract":"<jats:p> Today artificial neural networks are very useful to solve complex dynamic games of various types, i.e., to approximate optimal strategies with sufficient accuracy. Exemplarily four synthesis approaches for the solution of zero-sum, noncooperative dynamic games are outlined and discussed. Either value function, adjoint vector components or optimal strategies can be synthesized as functions of the state variables. In principle all approaches enable the solution of dynamic games. Nevertheless every approach has advantages and disadvantages which are discussed. The neural network training usually is very difficult and computationally very expensive. The coarse-grained parallelization FAUN 1.0-HPC-PVM of the advanced neurosimulator FAUN uses PVM subroutines and runs on heterogeneous and decentralized networks interconnecting general-purpose workstations, PCs and also high-performance computers. Computing times of days, weeks or months can be cut down to hours. An enhanced cornered rat game \u2014 formulated and analyzed in 1993 \u2014 serves as an example. Optimal strategies for cat and rat are synthesized. For this purpose open-loop representations of optimal strategies on an equidistant grid in the state space are used. An important end game modification is presented. <\/jats:p>","DOI":"10.1142\/s0219198905000569","type":"journal-article","created":{"date-parts":[[2005,9,23]],"date-time":"2005-09-23T01:05:08Z","timestamp":1127437508000},"page":"347-365","source":"Crossref","is-referenced-by-count":2,"title":["COARSE-GRAINED PARALLELIZATION OF THE ADVANCED NEUROSIMULATOR FAUN 1.0 WITH PVM AND THE ENHANCED CORNERED RAT GAME REVISITED"],"prefix":"10.1142","volume":"07","author":[{"given":"HANS-J\u00d6RG","family":"VON METTENHEIM","sequence":"first","affiliation":[{"name":"Institut f\u00fcr Wirtschaftsinformatik der Universit\u00e4t Hannover, K\u00f6nigsworther Platz 1, D-30167 Hannover, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"MICHAEL H.","family":"BREITNER","sequence":"additional","affiliation":[{"name":"Institut f\u00fcr Wirtschaftsinformatik der Universit\u00e4t Hannover, K\u00f6nigsworther Platz 1, D-30167 Hannover, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,20]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-8176-4755-1"},{"key":"rf2","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4899-3561-8","volume-title":"H\u221e-optimal Control and Related Minimax Design Problems: A Dynamic Game Approach","author":"Ba\u015far T.","year":"1991"},{"key":"rf3","volume-title":"Dynamic Noncooperative Game Theory","author":"Ba\u015far T.","year":"1982"},{"key":"rf4","volume-title":"Quantitative and Qualitative Games","author":"Blaqui\u00e8re A.","year":"1969"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1007\/s10957-004-1173-0"},{"key":"rf7","first-page":"483","volume":"107","author":"Breitner M. 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