  In the real world, agents or entities are in a continuous state of
interactions. These inter- actions lead to various types of complexity
dynamics. One key difficulty in the study of complex agent interactions is the
difficulty of modeling agent communication on the basis of rewards. Game theory
offers a perspective of analysis and modeling these interactions. Previously,
while a large amount of literature is available on game theory, most of it is
from specific domains and does not cater for the concepts from an agent- based
perspective. Here in this paper, we present a comprehensive multidisciplinary
state-of-the-art review and taxonomy of game theory models of complex
interactions between agents.

Computer Science and Game Theory;Artificial Intelligence;Multiagent Systems