DocumentCode :
2186102
Title :
Evolutionary Approach to Negotiation in Game AI
Author :
Iuhasz, Gabriel ; Munteanu, Victor Ion ; Negru, Viorel
Author_Institution :
Dept. of Comput. Sci., West Univ. of Timisoara, Timisoara, Romania
fYear :
2013
fDate :
23-26 Sept. 2013
Firstpage :
296
Lastpage :
302
Abstract :
As modern games become more and more sophisticated graphically, so does the level of artificial intelligence that animates them thus, the larger the game budget, the more work is put into improving the AI. Unfortunately many of these games feature AIs that are standalone and do not communicate with each other, they do not try to negotiate in order to improve their individual standing. The current work focuses on analysing existing game types in order to establish types of negotiation that can be achieved between AI entities. Moreover, an evolutionary approach which focuses on achieving negotiation between these entities and tackles the problem of having multiple negotiation items with discrete values is presented.
Keywords :
artificial intelligence; computer games; evolutionary computation; AI game; artificial intelligence; evolutionary approach; multiple negotiation items; Artificial intelligence; Contracts; Games; Genetic algorithms; Hidden Markov models; Sociology; Statistics; Artificial Intelligence; Evolutionary Algorithm; Games; Negotiation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2013 15th International Symposium on
Conference_Location :
Timisoara
Print_ISBN :
978-1-4799-3035-7
Type :
conf
DOI :
10.1109/SYNASC.2013.46
Filename :
6821163
Link To Document :
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