We identify challenges related to this planning problem, namely creating and destroy-ing objects, concurrent action generation and execution, and present ideas how to address them.

This problem class can be formulated as a resource accumulation and allocation problem where an agent has to decide what objects to produce at what time in order to meet one of two goals: either maximizing the number of produced objects in a given time period or producing a certain number of ob-jects as fast as possible. In this paper we approach the real-time planning problem by considering build-order optimiza-tion in real-time strategy games. A good example is modern video games in which it is apparent that com-puter characters lack human planning, learning, and rea-soning abilities. Human planning ability is therefore still considered superior. Planning in real-world domains poses a big challenge to current AI systems because of inadequate abstrac-tion and search mechanisms. The ability to plan becomes essential in unfamiliar environments where we cannot rely on previously learned action se-quences, but instead have to generate novel solutions by considering consequences of action choices on the fly. We are con-stantly involved in planning even when executing seem-ingly simple tasks such as driving to school. Planning is an important cognitive process.

Empire earth 1 vs 2