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theory studies how players can cooperate to reach a win-win situation when the
global gains are higher with cooperation than without. A frequently mentioned
drawback of game theoretic approaches is the perfect rationality assumption. In
order to select the best strategy, the player must know the entire environment as
well as the opponent's knowledge. Otherwise, it is not possible for the player to
estimate the most rational choice. Unfortunately, in real world situations, players
can hide some information from their partners in the decision-making process.
So an effective and systematic method to elicit and organize the information
from each team member is still in need to make rational group decision using
game theoretical approaches.
A way to overcome the game theory limitations described previously is to use
heuristic approaches. Heuristic-based negotiation is based on search strategies where
the objective, instead of finding the optimal solution, is to find a good solution
in a reasonable time. Multiple approaches can be used, depending on the search
strategy deployed. Stakeholders do not need to be perfectly rational, and informa-
tion can be kept private. Basically, the space of possible agreements is represented
by contracts having different values for each issue. Using its own utility function,
a stakeholder must compute the value of each contract. Proposals and counter-
proposals are exchanged over the different contracts and search terminates either
when the time limit has been reached or when a mutually acceptable solution has
been found. Kraus presented a review of applications of heuristics to negotiations
and pointed out where it represents an advantage over other approaches [Kraus
1998]. Klein worked on a simulated annealing-based approach for negotiation of
multi-interdependent issues in contracts [Klein et al. 2003]. Rahwan has worked on
defining a method for designing heuristics-based negotiation strategies for negotia-
tion agents by analyzing the environment and the agent capabilities [Rahwan et al.
2007]. While heuristic methods do indeed overcome some of the shortcomings of
game-theoretic approaches, they also have a number of disadvantages [Jennings et
al. 2001]. First, the models often lead to outcomes that are suboptimal, because the
information and space that the negotiation team can explore is always limited by
the design of the heuristics method, which is usually ad hoc. Second, because of the
ad hoc design of the heuristic method, it is very difficult to predict precisely how the
team and stakeholders will behave and there is usually no guaranteed solution at
the end of the execution of the heuristics. Consequently, these approaches usually
need extensive evaluation through simulations and empirical analysis, which is not
often available due to the resource limitation in engineering processes.
Argument-based negotiation approaches follow a generic structure of argu-
ments defined in [Toulmin 1958] which helps stakeholders lay out their negotiation
information and meta-information into various components, and this information
includes major claims, support data, and additional persuasive perspectives such as
justification, degree of desire, and rebuttal condition. In the negotiation approaches
presented previously, stakeholders cannot justify to their partner why they refuse
an offer or what part of the offer was problematic. Proposals do not include the
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