Evolving Behaviour-Dependent Strategies in Agent Negotiations
We use genetic algorithms to evolve trading strategies for iterative bilateral negotiations between buyers and sellers. In contrast to previous work we evolve purely reactive strategies that base decisions on memories of behaviour in previous negotiation rounds. A paper was written on this research and was published in the proceedings for the European Conference on Artificial Life 2013.
Programming languages and libraries: Python
Transdisciplinary tags: Complex Systems