Motivated Reinforcement Learning Curious Characters for Multiuser Games /

Motivated learning is an emerging research field in artificial intelligence and cognitive modelling. Computational models of motivation extend reinforcement learning to adaptive, multitask learning in complex, dynamic environments – the goal being to understand how machines can develop new skills an...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Merrick, Kathryn (Συγγραφέας), Maher, Mary Lou (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Non-Player Characters and Reinforcement Learning
  • Non-Player Characters in Multiuser Games
  • Motivation in Natural and Artificial Agents
  • Towards Motivated Reinforcement Learning
  • Comparing the Behaviour of Learning Agents
  • Developing Curious Characters Using Motivated Reinforcement Learning
  • Curiosity, Motivation and Attention Focus
  • Motivated Reinforcement Learning Agents
  • Curious Characters in Games
  • Curious Characters for Multiuser Games
  • Curious Characters for Games in Complex, Dynamic Environments
  • Curious Characters for Games in Second Life
  • Future
  • Towards the Future.