Setting the right price at a fuel station is a complex task involving numerous parameters. By using a hybrid agent architecture based on BDI and ANN you can model a fuel station agent that can learn to model its consumers. The fuel station agent can then use the learning from it’s consumer behaviour to detect anomalies in the environment and autonomously set its own price to influence the consumer and thereby optimize e.g. gross margin without sacrificing volume.
Imagine creating a truly customer-centric experience based on a customer’s unique needs and pains. Frodi will discuss using intentional data and behavioural insights to engage customers with relevant messages, at the right time – helping retailers to build trust and brand loyalty.