TY - GEN
T1 - Using GDL to represent domain knowledge for automated negotiations
AU - De Jonge, Dave
AU - Zhang, Dongmo
PY - 2016
Y1 - 2016
N2 - Current negotiation algorithms often assume that utility has an explicit representation as a function over the set of possible deals and that for any deal its utility value can be calculated easily. We argue however, that a more realistic model of negotiations would be one in which the negotiator has certain knowledge about the domain and must reason with this knowledge in order to determine the value of a deal, which is time-consuming. We propose to use Game Description Language to model such negotiation scenarios, because this may enable us to apply existing techniques from General Game Playing to implement domain-independent, reasoning, negotiation algorithms.
AB - Current negotiation algorithms often assume that utility has an explicit representation as a function over the set of possible deals and that for any deal its utility value can be calculated easily. We argue however, that a more realistic model of negotiations would be one in which the negotiator has certain knowledge about the domain and must reason with this knowledge in order to determine the value of a deal, which is time-consuming. We propose to use Game Description Language to model such negotiation scenarios, because this may enable us to apply existing techniques from General Game Playing to implement domain-independent, reasoning, negotiation algorithms.
KW - artificial intelligence
KW - game theory
KW - intelligent agents (computer software)
UR - http://handle.westernsydney.edu.au:8081/1959.7/uws:38756
U2 - 10.1007/978-3-319-46840-2_9
DO - 10.1007/978-3-319-46840-2_9
M3 - Conference Paper
SN - 9783319468396
SP - 134
EP - 153
BT - Autonomous Agents and Multiagent Systems: AAMAS 2016 Workshops, Visionary Papers, Singapore, May 9-10, 2016, Revised Selected Papers
PB - Springer
T2 - International Conference on Autonomous Agents and Multiagent Systems
Y2 - 9 May 2016
ER -