A Planning Based Agent Programming Language Supporting Environment Modeling

Over the years a lot of research has been carried out on designing new languages and platforms to program intelligent and autonomous agents. Most of the developed languages do not give agents the ability to plan ahead, but sometimes the execution of actions without planning results in the inability to achieve the goals. The languages that support planning, ignore the duration of agents' actions. Moreover, they do not allow modifications in a plan in case of unanticipated changes in the environment. This work tries to fill this gap by proposing an AOP language PLACE that endows the agents with planning capability. We are interested in the temporal planning of on the fly goals having different priorities. A coherent framework is proposed in which agents are able to generate, execute and monitor their temporal plans. A plan is repaired if some unanticipated changes in the environment cause the plan to become unfeasible. As the goals have different priorities, the framework also allows preemption of the low priority plans for the higher priority plans at run time. The environment is modeled visually to help the user simulate the behavior of agents and see the execution of agents' plans. Experimental results are presented to demonstrate the effectiveness of various algorithms.