what is artificial intelligence

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introduction to artificial intelligence for engineering


  • 1. What is artificial intelligence? shreya chakraborty

2. The physical symbol system set of entities==> symbols All symbols/instances related in some physical way. Processes(creation, modification, reproduction and destruction) shreya chakraborty 3. Intelligence requires knowledge Knowledge- 1. Voluminous 2. Hard to categorize 3. Constantly changing 4. Organisation different to usage shreya chakraborty 4. What is an AI technique? Should capture generalisation Understood by people who provide it Easily modified to correct errors and reflect changes Mostly accurate Overcome bulk possibilities to produce result shreya chakraborty 5. 3 important AI techniques? Search Use of knowledge Abstraction shreya chakraborty 6. 4 steps to solve a problem Define problem precisely Analyse problem Isolate and represent task knowledge necessary Choose best problem solving technique shreya chakraborty 7. State space representation Basis of AI methods Structure:- Formal definition for problem Explore space trying to find path from current state to goal state shreya chakraborty 8. State space problem Define state space (all possible configurations of relevant objects) Specify initial state Specify goal state Specify set of rules that define actions shreya chakraborty 9. Production System Rules : Applicability ->Operation Knowledge/Databases Control strategy Rule applier shreya chakraborty 10. Control Strategy requirements It should cause motion It should be systematic shreya chakraborty 11. Breadth-first Search shreya chakraborty 12. Depth-first Search shreya chakraborty 13. Heuristic Search Heuristic Knowledge incorporated in search in rules themselves or as a function shreya chakraborty 14. Heuristic function Problem description measures(numbers) F(x)=g(x)+h(x) shreya chakraborty 15. Problem characteristics Decomposable? Solution steps can be undone? Problems universe predictable? Good solution obvious? Desired solution a state or a path? Large amt of knowledge absolutely required to solve the problem/ Can computer take problem and return solution? shreya chakraborty 16. Issues in Search Program Design *instead of building entire tree, programs represent trees in rules implicitly, and generate what needs to be explored *forward vs backward reasoning *rule matching *knowledge representation problem and frame problem shreya chakraborty 17. Heuristic Search techniques 1. Depth First 2. Breadth First shreya chakraborty 18. 3. Generate and Test Generate solution Check to see if actually a solution by comparison If solution found quit, else repeat all steps shreya chakraborty 19. 4. Hill Climbing Simple Hill Climbing Steepest Ascent Hill Climbing shreya chakraborty 20. 5. Best First Search Or-graphs A* algorithm shreya chakraborty 21. using REDUCE-AND Use REDUCE on each immediate subgoal until there are no more subgoals, or until REDUCE finds a subgoal that is not satisfied. If REDUCE has found a subgoal that is not satisfied, announce that the goal is not satisfied; otherwise, announce that the goal is satisfied. using REDUCE-OR Use REDUCE on each subgoal until REDUCE finds a subgoal that is satisfied. If REDUCE has found a subgoal that is satisfied, announce that the goal is satisfied; otherwise, announce that the goal is not satisfied. shreya chakraborty 22. 6. Problem Reduction And-or graphs AO* algorithm shreya chakraborty 23. 8. Constraint Satisfaction shreya chakraborty 24. 8. Constraint Satisfaction shreya chakraborty 25. 9.Mean Ends Analysis To perform means-ends analysis, Until the goal is reached or no more procedures are available, - Describe the current state, the goal state, and the difference between the two. - Use the difference between the current state and goal state, possibly with the description of the current state or goal state, to select a promising procedure. - Use the promising procedure and update the current state. If the goal is reached, announce success; otherwise, announce failure. shreya chakraborty


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