Cantitate/Preț
Produs
Total produse
Vezi coșul
Monte Carlo Search: First Workshop, MCS 2020, Held in Conjunction with IJCAI 2020, Virtual Event, January 7, 2021, Proceedings de Tristan Cazenave

Monte Carlo Search: First Workshop, MCS 2020, Held in Conjunction with IJCAI 2020, Virtual Event, January 7, 2021, Proceedings: Communications in Computer and Information Science, cartea 1379

Editat de Tristan Cazenave, Olivier Teytaud, Mark H. M. Winands
en Limba Engleză Paperback – 16 oct 2021
This book constitutes the refereed proceedings of the First Workshop on Monte Carlo Search, MCS 2020, organized in conjunction with IJCAI 2020. The event was supposed to take place in Yokohama, Japan, in July 2020, but due to the Covid-19 pandemic was held virtually on January 7, 2021. 

The 9 full papers of the specialized project were carefully reviewed and selected from 15 submissions. The following topics are covered in the contributions: discrete mathematics in computer science, games, optimization, search algorithms, Monte Carlo methods, neural networks, reinforcement learning, machine learning.

Citește tot Restrânge

Din seria Communications in Computer and Information Science

Preț: 41085 lei

Preț vechi: 51357 lei
-20% Nou

Puncte Express: 616
Preț estimativ în valută:
7864€ • 8179$ • 6590£

Carte tipărită la comandă

Livrare economică 14-28 martie

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783030894528
ISBN-10: 3030894525
Pagini: 141
Ilustrații: IX, 141 p. 36 illus., 14 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.23 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Cham, Switzerland

Cuprins

The αµ Search Algorithm for the Game of Bridge.- Stabilized Nested Rollout Policy Adaptation.- zoNNscan: A Boundary-Entropy Index for Zone Inspection of Neural Models.- Ordinal Monte Carlo Tree Search.- Monte Carlo Game Solver.- Generalized Nested Rollout Policy Adaptation.- Monte Carlo Inverse Folding.- Monte Carlo Graph Coloring.- Enhancing Playout Policy Adaptation for General Game Playing.