Download presentation
Presentation is loading. Please wait.
Published byShauna Merritt Modified over 9 years ago
1
Blondie24 Presented by Adam Duffy and Josh Hill
2
Overview Introduction to new concepts Design of Blondie24 Testing and results Other approaches to checkers Other approaches to evolutionary computation Why is this important?
3
Neural Networks Nodes connected by links – Input nodes – Hidden nodes – Output nodes Links have weights
6
Evolutionary Computation Based on natural selection – Initialize population – Fitness function – Selection – Cross-over – Mutation
7
Design of Blondie24 Checkers neural network Values for input nodes – Red – positive – White – negative – Empty – zero Piece differential
10
Design of Blondie24 Connections between squares Subsections
14
Design of Blondie24 Search methods – Minimax – Alpha-beta pruning – Iterative deepening – Quiescent – Hash table of previously evaluated positions (maximum of 270,000)
15
Design of Blondie24 Initial population of 30 Each neural network plays 5 games as red – +1 for a win – 0 for a draw – -2 for a loss Top 15 kept, lowest 15 eliminated Copy top 15 and mutate the weights
17
Blondie24: Advantages Can learn new strategies Doesn’t have human biases
18
Blondie24: Disadvantages Long time Doesn’t make use of expert knowledge
19
Tests 400 MHz Pentium II 840 th generation Played games on zone.com 165 games total (84 as red, 81 as white)
20
Results zone.com rating: 2045.85 In top 500 of over 120,000 Better than 99.61% of registered players
23
Chinook Primary feature - piece count Looks for certain features Over 40,000 opening lines of play Every ending with <= 8 pieces Higher value to positions with more pieces Rated 2,814 at retirement in 1996
24
Different Evolutionary Approach Particle Swarm Optimizers (PSO) Each particle is moved closer to – Global best – Personal best so far
26
Other applications Industry, medicine, and defense Pattern recognition Cancer
27
More information Blondie 24: Playing at the Edge of AI by David B. Fogel Learning to play games using a PSO-based competitive learning approach by L. Messeischmidt and A.P. Engelbrecht The Advantages of Evolutionary Computation by David B. Fogel Solving the Game of Checkers by Jonathan Schaeffer and Robert Lake
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.