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Solving Problems by Searching

Solving Problems by Searching. 제 4 주 강의. Problem solving agent. What to do by finding sequences of actions that lead to desirable states the current state (environment), applicable operations, nest states Find a sequence of states maximizing the performance measure.

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Solving Problems by Searching

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  1. Solving Problems by Searching 제4주 강의

  2. Problem solving agent • What to do by finding sequences of actions that lead to desirable states • the current state (environment), applicable operations, nest states • Find a sequence of states maximizing the performance measure

  3. Problem solving • Goal formulation • Problem formulation :: the process of deciding what actions and states to consider • Missionary-carnival problem, 청소하는 로봇, 교육하는 시스템 등에 적용 • Sequence, solution

  4. Formulating Problems • Amounts of knowledge that an agent can have concerning its actions and the state that it is in  depends on the how the agent is connected to its environment through its percepts and actions

  5. Knowledge and problem type • Single-state problem ::: 에이전트는 세상을 정확히 인지하고, 행위의 결과도 정확히 안다. • Multiple-state problem ::: 행위의 결과는 정확히 알지만, 세상(환경)을 인식하는 데 한계가 있다; 또는 행위의 결과를 정확히 예측하지 못할 때; Murphy’s law

  6. Knowledge and problem type (cont.) • Contingency problem :::  Exact prediction is impossible  Solving this problem requires sensing during the execution phase;  Keep eyes open while walking or driving  Agents need to act before founding a guaranteed plan  Interleaving of search and execution

  7. Knowledge and problem type (cont.) • Exploration problem  No information about the effects of its actions  a strange country with no map  The agent must experiment, gradually discovering what its action and what sorts of states exists  Reinforcement learning

  8. Well-defined problems and solutions Initial state operation new state Successor function operation new state select a state goal test • state space  path, solution, path cost (g)

  9. Measuring problem-solving performance • Effectiveness of a search  Does it find a solution ?  Is it a good solution ?  What is the search cost associated with the time and memory to find a solution ?

  10. Example Problems • The 8(16)-puzzle problems 

  11. 문제 정의(8 puzzle) • <States, Operators, Goal test, Path cost> • Solving as search ::: Breadth first, Depth-first • Heuristics • 16 puzzle

  12. 8 Queens problem • Goal test ::: 8 queens on board, none attacked • Path cost ::: zero • States ::: any arrangement of 0 to 8 queens on board • Operators ::: add a queen to any square • Branch and Bound, Dynamic Programming • AI techniques

  13. Cryptarithmetic • FORTY 29785 + TEN 850 + TEN 850 -------- ------ SIXTY 31418 (F=2, O=9, R=7, etc.)

  14. The vacuum world • 복사하여 제공 후 설명 • Robot arm problem과 비교하여, 그림 3.7)처럼 결과 나오게 상태도를 그린다 (숙제)

  15. Other toy problems • Missionary and cannibals • Water jug

  16. Real world problems • Route finding • Travelling salesperson problem • VLSI design • Robot navigation • Assembly sequencing

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