Game theory models for communication between agents: a review
arXiv:1708.01636 · doi:10.1186/s40294-016-0026-7
Abstract
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.
31 pages, 7 figures
References in corpus (7)
- Agent-based computing from multi-agent systems to agent-based Models: a visual survey
- A novel agent-based simulation framework for sensing in complex adaptive environments
- Power Allocation Games for MIMO Multiple Access Channels with Coordination
- Pure Saddle Points and Symmetric Relative Payoff Games
- Cyclic game dynamics driven by iterated reasoning
- A zero-sum game between a singular stochastic controller and a discretionary stopper
- Structure of Extreme Correlated Equilibria: a Zero-Sum Example and its Implications