Incorporating Bayesian learning in agent-based simulation of stakeholders negotiation
An agent-based model was developed to simulate stakeholders negotiation regarding land development. A Bayesian learning approach was used to enable the Developer agent with learning capability. Two scenarios which included change in location and land-use composition were run both with and without learning capability. The results indicate that with Bayesian learning an agreement can be reached in a fewer number of negotiation rounds.
bayesian learning stakeholders negotiation agent-based model land development fuzziness