What is artificial intelligence
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The document discusses several key concepts in artificial intelligence including the physical symbol system, intelligence requiring knowledge, AI techniques like search and abstraction, the 4 steps to solve a problem using state space representation, and several search techniques like breadth-first search, depth-first search, heuristic search, and means-ends analysis. Production systems and heuristic functions are also covered.
What is artificial intelligence
- 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
- 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? •Problem’s 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