AI Planning and Team Abstractions

Many real-world problems rely on the collaboration of multiple agents. Making plans for these multiple agents such that the goal state can be achieved becomes more and more difficult as the number of objects to consider increases. The increase in the number of objects results in the exponential increase in time and space required to find a viable plan. By mapping each agent onto some team, creating an abstract plan, and applying the abstract plan to the concrete problem, we can produce plans that reach the goal state more quickly than by solving them directly. This is demonstrated by applying this method to multiple problems in a custom domain dubbed the “garden” domain.