Classical Planning

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Representation STRIPS STRIPS: Planning Domain [Wic11] Let L be a function-free first-order language. STRIPS planning domain on L is a restricted state-transition system Σ = (S, A, γ) such that: S is a set of STRIPS states, i.e. sets of ground atoms, A is a set of ground instances of some STRIPSplanning operators O γ : S × A → S where γ(s, a) = (s − effects − (a)) ∪ effects + (a) if a is applicable in s γ(s, a) = undefined otherwise S is closed under γ Radek Maˇrík (marikr@felk.cvut.cz) Classical Planning 15. dubna 2013 28 / 71
Representation STRIPS STRIPS: Planning Problem [Wic11] A STRIPS planning problem is a triple P = (Σ, si, g) where: Σ = (S, A, γ) is a STRIPS planning domain on some first-order language L si ∈ S is the initial state g is a set of ground literals describing the goal such that the set of goal states is Sg = {s ∈ S|s |= g} Radek Maˇrík (marikr@felk.cvut.cz) Classical Planning 15. dubna 2013 29 / 71
Page 1 and 2: Classical Planning Radek Maˇrík C
Page 3 and 4: Concept of Plan [Nau09] Concept of
Page 5 and 6: Concept of AI Planning Definition P
Page 7 and 8: Concept of AI Planning Conceptual M
Page 9 and 10: Concept of AI Planning Conceptual M
Page 11 and 12: Planning Task [Nau09] Concept of AI
Page 13 and 14: Types of Planners [Nau09] Domain-sp
Page 15 and 16: Classical Planning [Nau09] Concept
Page 17 and 18: Representation STRIPS Classical Rep
Page 19 and 20: Representation STRIPS STRIPS - stat
Page 21 and 22: Representation STRIPS STRIPS - Oper
Page 23: Representation STRIPS Applicability
Page 27 and 28: Overview of PDDL [Wic11] Representa
Page 29 and 30: Representation PDDL Monkey Planning
Page 31 and 32: Planning Methods Logics and Searchi
Page 33 and 34: Planning Methods Logics and Searchi
Page 35 and 36: Planning Methods State Space State-
Page 37 and 38: Planning Methods State Space Planni
Page 45 and 46: Backward Search [Wic11] 1 Backward-
Page 47 and 48: Planning Methods State Space Sussma
Page 49 and 50: Planning Methods State Space Sussma
Page 51 and 52: Summary Conclusions Summary What is
Page 53 and 54: PDDL Domains [Wic11] Pˇríloha PDD
Page 55 and 56: Pˇríloha PDDL Specification PDDL
Page 57 and 58: PDDL Action [Wic11] Pˇríloha PDDL
Page 59 and 60: PDDL Effects [Wic11] Pˇríloha PDD
Page 61 and 62: PDDL Problem [Wic11] Pˇríloha PDD
Page 63: References I Dana Nau. CMSC 722, ai

Classical Planning

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