Artificial Intelligence
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< Artificial intelligence‏‎

Before the optimal actions of a robot in a system can be determined, the system itself has to be understood. The subparts of the system can interact with each other and a model is used to formalize the values with mathematical equations. A typical example is a bathtube process, in which water floods into a tube.[1] Such a system can be visualized with a computer graphic and can be described with the QSIM tool.

Another slightly more powerful modeling technique is a randomized model.[2] Here is the idea to create a event transition graph which describes the working of the system with a probabilistic approach. This allows to describe a system even not all details are understood.

Qualitative reasoning

  • ontology "qualitative physics"[3]
  • grounding costmap[4]
  • "natural language instructions" interactive "Qualitative physics"
  • "hierarchical task network" "qualitative physics"
  • qualitative kinematics

References

  1. Hocaoğlu, Mehmet Fatih. "Qualitative Reasoning for Quantitative Simulation." Modelling and Simulation in Engineering 2018 (2018).
  2. Eveillard, Damien, et al. "Probabilistic modeling of microbial networks for integrating partial quantitative knowledge within the nitrogen cycle." Frontiers in microbiology 9 (2018): 3298.
  3. OUR-K framework, The Kautham Project
  4. “Learning Qualitative Spatial Relations for Robotic Navigation”, page 3 shows an example for a cost map
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