The *-Minimax Search Procedure for Trees Containing Chance Nodes
By Bruce W. Ballard. 1983
Subfields: Game & Decision Theory, Algorithms & Complexity
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Game & Decision Theory
- Karl Tuyls
- Julien Pérolat
- Jean-Baptiste Lespiau
- Shayegan Omidshafiei
- Marc Lanctot
- Vinícius Flores Zambaldi
- Daniel Hennes
- Dustin Morrill
In Algorithms & Complexity
- Richard Dearden
- Jonathan Rubin
- Craig Boutilier
- Marc Lanctot
- Ian D. Watson
- Matthew Lai
- Julian Schrittwieser
Citations in the corpus
- OpenSpiel: A Framework for Reinforcement Learning in Games (2019, methodology): “Alpha-beta style cut-offs could also be applied using ∗-minimax [5], but it is not currently implemented.”
- Abstraction and Approximate Decision-Theoretic Planning (1997, background): “This is the basis of, for instance, Ballard's ?-minimax search [1].”
- Computer poker: A review (2011, background): “The expected value at a chance node is given by weighting each outcome’s utility by its probability of occurrence and summing over all the possible outcomes [6].”