%0 Book Section %B Parallel Problem Solving from Nature – PPSN XIV: 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings %D 2016 %T Tutorials at PPSN 2016 %A Doerr, Carola %A Bredeche, Nicolas %A Alba, Enrique %A Bartz-Beielstein, Thomas %A Brockhoff, Dimo %A Doerr, Benjamin %A Eiben, Gusz %A Epitropakis, Michael G. %A Fonseca, Carlos M. %A Guerreiro, Andreia %A Haasdijk, Evert %A Heinerman, Jacqueline %A Hubert, Julien %A Lehre, Per Kristian %A Malagò, Luigi %A Merelo, J. J. %A Miller, Julian %A Naujoks, Boris %A Oliveto, Pietro %A Picek, Stjepan %A Pillay, Nelishia %A Preuss, Mike %A Ryser-Welch, Patricia %A Squillero, Giovanni %A Stork, Jörg %A Sudholt, Dirk %A Tonda, Alberto %A Whitley, Darrell %A Zaefferer, Martin %E Handl, Julia %E Hart, Emma %E Lewis, Peter R. %E López-Ibáñez, Manuel %E Ochoa, Gabriela %E Paechter, Ben %X PPSN 2016 hosts a total number of 16 tutorials covering a broad range of current research in evolutionary computation. The tutorials range from introductory to advanced and specialized but can all be attended without prior requirements. All PPSN attendees are cordially invited to take this opportunity to learn about ongoing research activities in our field! %B Parallel Problem Solving from Nature – PPSN XIV: 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings %I Springer International Publishing %C Cham %P 1012–1022 %@ 978-3-319-45823-6 %G eng %U http://dx.doi.org/10.1007/978-3-319-45823-6_95 %R 10.1007/978-3-319-45823-6_95 %0 Conference Paper %B Applications of Evolutionary Computation %D 2011 %T Weighted Markov Chain Model for Musical Composer Identification %A M. A. Kaliakatsos-Papakostas %A M. G. Epitropakis %A M. N. Vrahatis %E Di Chio, Cecilia %E Brabazon, Anthony %E Di Caro, Gianni %E Drechsler, Rolf %E Farooq, Muddassar %E Grahl, Jörn %E Greenfield, Gary %E Prins, Christian %E Romero, Juan %E Squillero, Giovanni %E Tarantino, Ernesto %E Tettamanzi, Andrea %E Urquhart, Neil %E Uyar, A. %X Several approaches based on the ‘Markov chain model’ have been proposed to tackle the composer identification task. In the paper at hand, we propose to capture phrasing structural information from inter onset and pitch intervals of pairs of consecutive notes in a musical piece, by incorporating this information into a weighted variation of a first order Markov chain model. Additionally, we propose an evolutionary procedure that automatically tunes the introduced weights and exploits the full potential of the proposed model for tackling the composer identification task between two composers. Initial experimental results on string quartets of Haydn, Mozart and Beethoven suggest that the proposed model performs well and can provide insights on the inter onset and pitch intervals on the considered musical collection. %B Applications of Evolutionary Computation %I Springer Berlin / Heidelberg %G eng %R 10.1007/978-3-642-20520-0_34