AI_Session 25 classical planning.pptx
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The document discusses classical planning approaches in artificial intelligence. It covers topics like planning algorithms, representation of states, goals, and actions. Classical planning assumes fully observable, deterministic, static, and discrete environments. Planning involves finding a sequence of actions to achieve a goal state from the initial state. Different planning approaches like state space search, planning graphs, and logical planning were discussed. Examples like the vacuum cleaner agent and box world domain were provided to illustrate classical planning concepts and representations.
AI_Session 25 classical planning.pptx
- 1. ARTIFICAL INTELLIGENCE (R18 III(II Sem)) Department of computer science and engineering (AI/ML) Session 25 by Asst.Prof.M.Gokilavani VITS 6/11/2023 Dpaertment of CSE ( AL & ML) 1
- 2. TEXTBOOK: • Artificial Intelligence A modern Approach, Third Edition, Stuart Russell and Peter Norvig, Pearson Education. REFERENCES: • Artificial Intelligence, 3rd Edn, E. Rich and K.Knight (TMH). • Artificial Intelligence, 3rd Edn, Patrick Henny Winston, Pearson Education. • Artificial Intelligence, Shivani Goel, Pearson Education. • Artificial Intelligence and Expert Systems- Patterson, Pearson Education. 6/11/2023 Dpaertment of CSE ( AL & ML) 2
- 3. Topics covered in session 25 6/11/2023 Dpaertment of CSE ( AL & ML) 3 Planning Classical Planning: Definition of Classical Planning, Algorithms for Planning with State-Space Search, Planning Graphs, other Classical Planning Approaches, Analysis of Planning approaches. Planning and Acting in the Real World: Time, Schedules, and Resources, Hierarchical Planning, Planning and Acting in Nondeterministic Domains, Multi agent Planning.
- 4. Planning Agent Eg: vacuum cleaner 6/11/2023 4 Dpaertment of CSE ( AL & ML)
- 5. Purpose of Planning • The purpose of planning is to find a sequence of actions that achieves a given goal when performed starting in a given state. • In other words, given a set of operator instances (defining the possible primitive actions by the agent), an initial state description, and a goal state description or predicate, the planning agent computes a plan. • Start Final Operator Instances PLAN. 6/11/2023 5 Dpaertment of CSE ( AL & ML)
- 6. Type of Environments – fully observable • we see everything that matters – deterministic • the effects of actions are known exactly – static • no changes to environment other than those caused by agent actions – discrete • changes in time and space occur in quantum amounts – single agent • no competition or cooperation to account for 6/11/2023 6 Dpaertment of CSE ( AL & ML)
- 7. What is plan? • The task of coming up with a sequence of actions that will achieve a goal is called Planning. • Planning Problems so far: – search-based problem solving – logical planning • Consider only environment that are fully observable, deterministic, finite, static (change happens only when the agent acts), and discrete (in time, action, objects and effects). These are called Classical Planning. 6/11/2023 7 Dpaertment of CSE ( AL & ML)
- 8. State and Goal: Classical planning 6/11/2023 8 Dpaertment of CSE ( AL & ML)
- 9. Non classical planning • Non classical planning is for partially observable or stochastic environments and involves a different set of algorithms and agent designs. 6/11/2023 9 Dpaertment of CSE ( AL & ML)
- 10. Why we need planning? • Intelligent agents must operate in the world. – Take intelligent actions – Compose actions together to achieve complex goals • Change the world to suit the needs. Agents need to reason about what the world will be like after executing a sequence of actions – Need to reason about dynamic environment 6/11/2023 Dpaertment of CSE ( AL & ML) 10
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- 12. Planning algorithm • Generate a goal to achieve • Construct a plan to achieve goal from current state • Execute plan until finished • Begin again with new goal 6/11/2023 Dpaertment of CSE ( AL & ML) 12
- 13. The language planning problems • Planning algorithms should take advantage of the logical structure of the problem. • The key is to find a language that is expressive enough to describe a wide variety problems, but restrictive enough to allow efficient algorithms to operate over it. • The problem should be expressed in a suitable logical language. • Planning is considered different from problem solving because of the difference in the way they represent states, goals, actions, and the differences in the way they construct action sequences. 6/11/2023 Dpaertment of CSE ( AL & ML) 13
- 14. Representation of states – Planners decompose the world into logical conditions and represent a state as conjunction of positive literals – Example; prepositional logic P V Q Representation of goals – A goal is partially specified state, represented as a conjunction of positive ground literals, such as 𝐏 ∧Q. – A propositional state s satisfies a goal g if s contains all the atoms in g. – Example; P∧ 𝑸 ∧R satisfies the goal 𝐏 ∧Q Representation of actions – An action is specified in terms of the pre conditions that must hold before it can be executed and the effects that ensue when it is executed. – Example: Action(Fly(p,From,To), – PRECOND: At(p, from) ∧ Plane(p) ∧ Airport(from) ∧ Airport(to), EFFECT: ~At(p,from) ∧ At(p,to)) 6/11/2023 Dpaertment of CSE ( AL & ML) 14
- 15. Action schema • Action schema, meaning that it represents a number of different actions that can be derived by instantiating the variables p, from and to different constants. In general action schema consists of three parts: – The action name and parameter list – The precondition is a conjunction of function-free positive literals stating what must be true in state before the actions can be executed. – The effect is a conjunction of function-free literals describing how the state changes when the action is executed. 6/11/2023 Dpaertment of CSE ( AL & ML) 15
- 16. Example : Box world 6/11/2023 Dpaertment of CSE ( AL & ML) 16
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- 19. Topics to be covered in next session 26 • Planning state space Thank you!!! 6/11/2023 Dpaertment of CSE ( AL & ML) 19