Techniques in Automated Planning
Automated planning techniques can be broadly classified into two categories: deterministic and non-deterministic.
- Deterministic planning assumes a predictable environment where every action has a guaranteed outcome, suitable for static or highly controlled environments.
- Non-deterministic (or probabilistic) planning, on the other hand, deals with uncertainty in action outcomes, requiring more complex algorithms like Markov decision processes (MDP) or Partially Observable Markov Decision Processes (POMDP).
Automated Planning in AI
Automated planning is an essential segment of AI. Automated planning is used to create a set of strategies that will bring about certain results from a certain starting point. This area of AI is critical in issues to do with robotics, logistics and manufacturing, game playing as well as self-controlled systems.
Automated planning is a way of making efficient and effective decisions in complex systems by achieving the goal of a decision-processing method that can work in a constantly changing world. The article delves into the essence of automated planning, its mechanisms, applications, and the challenges it faces.
Table of Content
- The Essence of Automated Planning
- Techniques in Automated Planning
- Automated Planning in AI
- Example of Automated Planning in Robotics
- Application of Automated Planning in AI
- Conclusion