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Case-based Reasoning

Case-based Reasoning. Introduction. What is CBR? Case-based reasoning is a problem solving paradigm. CBR also is an approach to incremental, sustained learning. When a problem is successfully solved When an attempt to solve a problem fails as well.

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Case-based Reasoning

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  1. Case-based Reasoning

  2. Introduction What is CBR? • Case-based reasoning is a problem solving paradigm. • CBR also is an approach to incremental, sustained learning. • When a problem is successfullysolved • When an attempt to solve a problem failsas well.

  3. Central tasks of all case-based reasoningmodels • Identify the current problem situation. • Find a past case similar to the new one. • Use that case to suggest a solution to the current problem. • Evaluate the proposed solution, and update the system by learning from this experience.

  4. 1. Representation  of  Cases • Deciding what to store in a case. • Finding an appropriate structure. • Deciding how the case memory should be organized . • How to integrate the case memory structure into a model of general domain knowledge.

  5. The Dynamic Memory Model

  6. The Category & Exemplar Model

  7. 2. Case Retrieval • Identify Feature • Initially  Match • Select

  8. 3. Case Reuse • Copy • Adapt • Transformational reuse • Derivational reuse

  9. 4. Case Revision • Evaluate solution • Repair fault

  10. 5.Case Retainment  Learning • Extract • Index • Integrate

  11. Case-based planning • Case-based planning is the reuse of past successful plans in order to solve new planning problems. • Extracting behavioral knowledge from an expert in form of individual cases. This knowledge can be reused to achieve the specific open goals in the current plan.

  12. On-line Case-based Plan Adaptation • Allows the AI engine to create and adapt plans in an efficient and effective manner while performing the task.

  13. Case-Based Planning in WARGUSDarmok system • Darmok was designed to play the game of WARGUS and apply the plan adaptation techniques. • Darmok learns behaviors from expert demonstrations, and then uses case-based planning to play the game reusing the learnt behaviors.

  14. Darmok system

  15. Plan Representation Language • A behavior has two main parts: • The declarative part • The procedural part • The state of a behavior • Goal

  16. Run-Time Plan Expansion and Execution

  17. On-Line Case-Based Plan Adaptation • Plan Dependency Graph Generation • Precondition-success condition matcher (ps-matcher). • Removal of unnecessary actions • Adaptation for unsatisfied preconditions

  18. Plan Dependency Graph • Taking the success conditions of the root of the plan. • Finding out which actions in the plan contribute to the achievement of these success conditions. • These actions are called direct sub-plans for the sub-goal. • 4- All direct sub-plans are added to the plan dependency graph. Then the plan dependency graph generator analyzes the preconditions of each of these direct sub-plans.

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