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Automated planning considering event based spatial object interactions using spatio-temporal reasoning

机译:使用时空推理考虑基于事件的空间对象交互的自动规划

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Knowledge Representation and Reasoning (KRR) in the domain of planning involve knowledge computing on expressiveness of action sequence that leads to desired goal state. An agent is an entity that perceives the environment. The essence of action sequence relies on representation of agent's perception towards the goal. The agent in an environment act on percept sequence to accomplish the states those lead to the goal state. Spatio-temporal reasoning based automated planning is proposed in which object interaction based on spatial relations in temporal scale is a state, representing an event and transition among the states are modeled using Finite State Machine (FSM) to extract the action sequence that accomplishes the task. Problem solving approach using Planning Domain Definition Language (PDDL) is significant when domain definitions involving agent's preconditions, actions and effects are required to model the percept sequence. PDDL is used to model agent's percept sequence with preconditions on actions and its effects. The development of proposed method into an autonomous planning agent with real time task orientation is left to work in future.
机译:规划领域的知识表示和推理(KRR)涉及对导致期望目标状态的动作序列表达能力的知识计算。代理是感知环境的实体。动作序列的本质取决于代理人对目标的看法的表示。环境中的主体按感知顺序起作用,以完成导致目标状态的状态。提出了一种基于时空推理的自动计划,其中基于时空空间关系的对象交互是一个状态,表示一个事件,并且使用有限状态机(FSM)对状态之间的转换进行建模,以提取完成任务的动作序列。当需要涉及主体先决条件,行动和效果的领域定义来建模感知序列时,使用规划领域定义语言(PDDL)的问题解决方法就非常重要。 PDDL用于对行为及其效果的先决条件建模代理的感知序列。将所提出的方法发展为具有实时任务导向的自治计划代理,将在将来继续工作。

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