Making autonomous agents effective in real-life applications requires the ability to decide at run-time and a high degree of adaptability to unpredictable and uncontrollable events. Reacting to events is still a fundamental ability for an agent, but it has to be boosted up with proactive behaviors that allow the agent to explore alternatives and decide at run-time for optimal solutions. This calls for a continuous planning as part of the deliberation process that makes an agent able to reconsider plans on the base of temporal constraints and changes of the environment. Online planning literature offers several approaches used to select the next action on the base of a partial exploration of the solution space. In this paper, we propose a BDI continuous temporal planning framework, where interleave planning and execution loop is used to integrate online planning with the BDI control-loop. The framework has been implemented with the ROS2 robotic framework and planning algorithms offered by JavaFF.

翻译：实现自主智能体在现实应用中的有效性，要求具备运行时决策能力以及对不可预测、不可控事件的高度适应性。事件响应仍是智能体的基本能力，但需通过前瞻性行为加以增强——使智能体能探索备选方案，并在运行时选择最优解。这要求将持续规划纳入推理过程，使智能体能够基于时间约束与环境变化重新考虑规划。在线规划领域已有多种方法，通过部分解空间探索来实现下一步动作选择。本文提出一种BDI持续时间规划框架，采用规划与执行交织循环，将在线规划与BDI控制回路相融合。该框架已基于ROS2机器人框架及JavaFF提供的规划算法实现。