Design and build a knowledge-based intelligent system

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Reference no: EM131897079

Introduction to AI Project -

For this project, you will design and build a knowledge-based intelligent system that collects user preferences and reasons about them.

1. Requirements -

1. The system should have an easy-to-use GUI (using the Python Tkinter module) for collecting names of attributes and their values, hard constraints, and preferences. The system should also allow for reading in these input from files. (See section 3 for formats of these files.)

  • Attributes (A) in this project are going to be binary.
  • Hard constraints (H) are represented as propositional formulas in the Conjunctional Normal Form (CNF).
  • The system should support preferences (T) in the preference languages we discussed in class: Penalty Logic and Possibilistic Logic. Formulas involved in the preference theories are of CNF as well.

2. The system should support the following reasoning tasks:

  • Existence of feasible objects: decide whether there are feasible objects w.r.t H, that is, whether there are models of H that are truth assignments making H true.
  • Exemplification: generate, if possible, two random feasible objects, and show the preference between the two (strict preference, equivalence, or incomparable).
  • Optimization: find an optimal object w.r.t T.
  • Omni-optimization: find all optimal objects w.r.t T.

3. The system should take advantage of the clasp system, a SAT solver that takes a propositional formula in CNF and computes its models. It can be used to compute feasible objects for H, check if a truth assignment satisfies a formula, etc. A short tutorial will be posted shortly.

4. For testing, the system should solve an instance, developed by you, that contains at least 6 hard constraints and at least 6 preference rules over at least 8 attributes. Also use this instance when demonstrating your system

2. Deliverables -

Zip the following to name [your-last-name] Project3.zip and submit to Canvas.

1. A text file with description of the instance (attributes and their values, hard constraints, and preferences) you used for testing.

2. A directory that contains all your source codes.

3. A README file that contains instructions to build and run your system.

4. A PDF report that describes how your system works and shows the testing results using the test instance (e.g., screen shots of various steps).

Attachment:- Assignment File.rar

Reference no: EM131897079

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Reviews

len1897079

3/12/2018 12:57:24 AM

Clasp is a SAT solver that takes a Boolean formula in the conjunctive normal form (CNF) and decides if it is satis?able. In case satis?able, clasp computes one, or even all, satisfying truth assignments. In case unsatis?able, clasp computes UNSAT. Download version 3.3.2. By Mar. 16, you will need to meet me to discuss the progress. You will make individual appointments with me by email. Failure of this will result in deduction in the project grade.

len1897079

3/12/2018 12:57:19 AM

Submit a text file with description of the instance (attributes and their values, hard constraints, and preferences) you used for testing. A README file that contains instructions to build and run your system and A PDF report that describes how your system works and shows the testing results using the test instance (e.g., screen shots of various steps).

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