MGP: Un algorithme de planification temps réel prenant en compte l'évolution dynamique du but

10/22/2018
by   Damien Pellier, et al.
0

Devising intelligent robots or agents that interact with humans is a major challenge for artificial intelligence. In such contexts, agents must constantly adapt their decisions according to human activities and modify their goals. In this paper, we tackle this problem by introducing a novel planning approach, called Moving Goal Planning (MGP), to adapt plans to goal evolutions. This planning algorithm draws inspiration from Moving Target Search (MTS) algorithms. In order to limit the number of search iterations and to improve its efficiency, MGP delays as much as possible triggering new searches when the goal changes over time. To this purpose, MGP uses two strategies: Open Check (OC) that checks if the new goal is still in the current search tree and Plan Follow (PF) that estimates whether executing actions of the current plan brings MGP closer to the new goal. Moreover, MGP uses a parsimonious strategy to update incrementally the search tree at each new search that reduces the number of calls to the heuristic function and speeds up the search. Finally, we show evaluation results that demonstrate the effectiveness of our approach.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/25/2015

Plan Explicability and Predictability for Robot Task Planning

Intelligent robots and machines are becoming pervasive in human populate...
research
07/05/2022

Plan Execution for Multi-Agent Path Finding with Indoor Quadcopters

We study the planning and acting phase for the problem of multi-agent pa...
research
05/11/2014

Using Tabled Logic Programming to Solve the Petrobras Planning Problem

Tabling has been used for some time to improve efficiency of Prolog prog...
research
10/19/2018

Planification par fusions incrémentales de graphes

In this paper, we introduce a generic and fresh model for distributed pl...
research
04/28/2020

Finding Macro-Actions with Disentangled Effects for Efficient Planning with the Goal-Count Heuristic

The difficulty of classical planning increases exponentially with search...
research
08/24/2020

Feature Guided Search for Creative Problem Solving Through Tool Construction

Robots in the real world should be able to adapt to unforeseen circumsta...
research
03/30/2022

Anticipatory Counterplanning

In competitive environments, commonly agents try to prevent opponents fr...

Please sign up or login with your details

Forgot password? Click here to reset