Real time planning in N-dim state space

Abstract

This paper presents the actual work in real-time planning as search [1] [2]. Based in this work we tried to solve the path planning in numerical state space. We found that precision, performance, and time were very linked. In real-time problem solving, the agent can fall in traps made of forbidden zones and to go out it, have to spend too much computing time. To solve this problem we propose a multilayer inference based in subgoals computation. An architecture based in two agents, one for low level task with the maximum precision and other for subgoals computation is proposed here.