The Byzantine Generals Problem
ACM Transactions on Programming Languages and Systems (TOPLAS)
Distributed Algorithms
Dynamic populations in genetic algorithms
Proceedings of the 2008 ACM symposium on Applied computing
Dynamic hybrid fault models and the applications to wireless sensor networks (WSNs)
Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems
New approaches to reliability and survivability with survival analysis, dynamic hybrid fault models, and evolutionary game theory
Insect sensory systems inspired computing and communications
Ad Hoc Networks
Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies
AICI '09 Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence
The Handicap Principle for Trust in Computer Security, the Semantic Web and Social Networking
WISM '09 Proceedings of the International Conference on Web Information Systems and Mining
AICI '09 Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence
The Handicap Principle for Trust in Computer Security, the Semantic Web and Social Networking
WISM '09 Proceedings of the International Conference on Web Information Systems and Mining
International Journal of Bio-Inspired Computation
International Journal of Information and Computer Security
Hi-index | 0.00 |
Competition , cooperation and communication are the three fundamental relationships upon which natural selection acts in the evolution of life. Evolutionary game theory (EGT) is a 'marriage' between game theory and Darwin's evolution theory; it gains additional modeling power and flexibility by adopting population dynamics theory. In EGT, natural selection acts as optimization agents and produces inherent strategies, which eliminates some essential assumptions in traditional game theory such as rationality and allows more realistic modeling of many problems. Prisoner's Dilemma (PD) and Sir Philip Sidney (SPS) games are two well-known examples of EGT, which are formulated to study cooperation and communication , respectively. Despite its huge success, EGT exposes a certain degree of weakness in dealing with time-, space- and covariate-dependent (i.e., dynamic ) uncertainty , vulnerability and deception . In this paper, I propose to extend EGT in two ways to overcome the weakness. First, I introduce survival analysis modeling to describe the lifetime or fitness of game players . This extension allows more flexible and powerful modeling of the dynamic uncertainty and vulnerability (collectively equivalent to the dynamic frailty in survival analysis). Secondly, I introduce agreement algorithms , which can be the Agreement algorithms in distributed computing (e.g., Byzantine Generals Problem [6][8], Dynamic Hybrid Fault Models [12]) or any algorithms that set and enforce the rules for players to determine their consensus. The second extension is particularly useful for modeling dynamic deception (e.g., asymmetric faults in fault tolerance and deception in animal communication). From a computational perspective, the extended evolutionary game theory (EEGT) modeling, when implemented in simulation, is equivalent to an optimization methodology that is similar to evolutionary computing approaches such as Genetic algorithms with dynamic populations [15][17].