Name
Abstract | ||
|---|---|---|
This paper proposes an evolutionary algorithm for evolving game bots that eschews an explicit fitness function using instead a match between individuals called joust and implemented as a selection mechanism where only the winner survives. This algorithm has been designed as an optimization approach to generate the behavioural engine of bots for the RTS game Planet Wars using Genetic Programming and has two objectives: first, to deal with the noisy nature of the fitness function and second, to obtain more general bots than those evolved using a specific opponent. In addition, avoiding the explicit evaluation step reduce the number of combats to perform during the evolution and thus, the algorithm time consumption is decreased. Results show that the approach performs converges, is less sensitive to noise than other methods and it yields very competitive bots in the comparison against other bots available in the literature. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-31204-0_35 | Lecture Notes in Computer Science |
Field | DocType | Volume |
Evolutionary algorithm,Computer science,Genetic programming,Fitness function,Artificial intelligence | Conference | 9597 |
ISSN | Citations | PageRank |
0302-9743 | 2 | 0.41 |
References | Authors | |
12 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| A. Fernández-Ares | 1 | 59 | 8.59 |
| Pablo García-sánchez | 2 | 182 | 32.32 |
| Antonio Miguel Mora | 3 | 314 | 42.81 |
| Pedro A. Castillo | 4 | 177 | 33.68 |
| Juan J. Merelo | 5 | 177 | 26.16 |