Action and Perception in Multi-Agent Programming Languages: From Exogenous to Endogenous Environments

The action and perception models adopted by state-of-the-art agent programming languages – in the context of Multi-Agent System (MAS) programming – have been conceived mainly to work with exogenous environments, i.e. physical or computational environments completely external to the MAS and then out of MAS design and programming. In this paper we discuss the limits of adopting such models when endogenous environments are considered, i.e. computational environments – often referred also as application environments – that are designed and programmed by MAS developers as a first-class abstraction to encapsulate functionalities useful for agent individual and cooperative activities. In the paper we describe an action and perception model for agent programming languages specifically conceived to be effective for endogenous environments and we discuss its evaluation using CArtAgO environment technology. On the agent side, we focus our attention on programming languages based on the BDI (Belief-Desire-Intention) model, taking Jason, 2APL and GOAL as reference case studies.