Agent programming language with incomplete knowledge - AgentSpeak(I)

This paper proposes an agent programming language called AgentSpeak(l). This new language allows agent programs (1) to effectively perform while having incomplete knowledge of the environment. (2) to detect no-longer possible goals and re-plan these goals correspondingly. and (3) to behave reactively to changes of environment. Specifically, AgentSpeak(l) uses default theory as agent belief theory, agent always act with preferred default extension at current time point (i.e. preference may changes over time). A belief change operator for default theory is also provided to assist agent program to update its belief theory. Like other BDI agent programming languages, AgentSpeak(l) uses semantics of transitional system. It appears that the language is well suited for intelligent applications and high level control robots, which are required to perform in highly dynamic environment.