学習と計画の限界：最小十分情報遷移システム
The Limits of Learning and Planning: Minimal Sufficient Information Transition Systems
ロボットの限られた知覚・記憶・計算・行動能力を考慮し、方策や計画を情報状態上の遷移システムとして捉え、最小情報遷移システムの存在と一意性を理論的に示した。
著者: Basak Sakcak, Vadim Weinstein, Steven M. LaValle
分類: cs.RO
原文アブストラクト
In this paper, we view a policy or plan as a transition system over a space of information states that reflect a robot's or other observer's perspective based on limited sensing, memory, computation, and actuation. Regardless of whether policies are obtained by learning algorithms, planning algorithms, or human insight, we want to know the limits of feasibility for given robot hardware and tasks. Toward the quest to find the best policies, we establish in a general setting that minimal information transition systems (ITSs) exist up to reasonable equivalence assumptions, and are unique under some general conditions. We then apply the theory to generate new insights into several problems, including optimal sensor fusion/filtering, solving basic planning tasks, and finding minimal representations for feasible policies.
