Improving the contextual selection of BDI plans by incorporating situated experiments

Abstract

This paper is dedicated to intentional BDI agents evolving in ambient environment. The planning management framework we propose, looks for efficient guidance to improve the satisfaction of the agent’s intentions with respect to the possible concurrent plans and the current context of the agent. Adopting the idea that ”location” and ”time” are key stones information in the activity of the agent, we show how to enforce guidance by ordering the different possible plans. As a major contribution, we demonstrate two original utility functions that are designed from the past-experiences of the action executions, and that can be combined accordingly to the current balance policy of the agent.