you can now donate with bitcoin or your bank card by clicking the piggy icon under the logo

  • Get the best VPN on the market with 66% Discount!
Education » Literary
Sequential Decision-Making in Musical Intelligence screenshot
English | ISBN: 303030518X | 2020 | 206 pages | PDF | 4 MB
Over the past 60 years, artificial intelligence has grown from an academic field of research to a ubiquitous array of tools used in everyday technology. Despite its many recent successes, certain meaningful facets of computational intelligence have yet to be thoroughly explored, such as a wide array of complex mental tasks that humans carry out easily, yet are difficult for computers to mimic. A prime example of a domain in which human intelligence thrives, but machine understanding is still fairly limited, is music.

Over recent decades, many researchers have used computational tools to perform tasks like genre identification, music summarization, music database querying, and melodic segmentation. While these are all useful algorithmic solutions, we are still a long way from constructing complete music agents able to mimic (at least partially) the complexity with which humans approach music.

One key aspect that hasn't been sufficiently studied is that of sequential decision-making in musical intelligence. Addressing this gap, the book focuses on two aspects of musical intelligence: music recommendation and multi-agent interaction in the context of music. Though motivated primarily by music-related tasks, and focusing largely on people's musical preferences, the work presented in this book also establishes that insights from music-specific case studies can also be applicable in other concrete social domains, such as content recommendation.

Showing the generality of insights from musical data in other contexts provides evidence for the utility of music domains as testbeds for the development of general artificial intelligence techniques.
Ultimately, this thesis demonstrates the overall value of taking a sequential decision-making approach in settings previously unexplored from this perspective.

download from free file storage
click to show download links

FileHost Included:
Uploaded | Rapidgator | Rockfile | Katfile | Douploads | Clicknupload
download from Usenet - 14 days free access +300GB Decision-Making in Musical Intelligence
download from any file hoster with just one LinkSnappy account
download from more than 100 file hosters at once with LinkSnappy.


  Contributor 2.11.2014 1633 9033
Uploaded | Rapidgator | Rockfile | Uploadboy | Katfile | Clicknupload | Nitroflare
  Resident 1.10.2013 4696 9373
  Resident 5.12.2012 756 15716
Uploaded | Rockfile | Rapidgator | Douploads | Clicknupload
  Member 1.09.2015 438 1541
  Banned 3.08.2012 75 17924
the Comment has been Removed
  Resident 17.04.2012 447
funny, many weeks ago I have did a research in AI compositon, the main goal is replace the composer, input a customer commands and output a work, and use computer to reach maximal of amount of possible results and super fast output speed, with aesthetics on human world.
the critical problem in here was 2, how to reach what you want, and how to realize it, it fuzzy. so in digital area it's the decision-making, yes, in the title, but not things they said in the book. in digital everything was duality, t or f, 0 or 1, or need or need not, inner or outer, that mean, you can got the final range of music you make, even it was all without number. now I am in the near final step, aesthetics and musics, aesthetics competings, and make a app.

Spread the Word