Classical Planning

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Planning Methods Logics and Searching Planning - a problem specification in Prolog % Farmer, Wolf, Goat, Cabbage % =========================== initialState([n,n,n,n]). finalState([s,s,s,s]). nextState(S, S1) :- move(S, S1), safe(S1). move([F, W, G, C], [F1, W, G, C]) :- cross(F, F1). move([F, F, G, C], [F1, F1, G, C]) :- cross(F, F1). move([F, W, F, C], [F1, W, F1, C]) :- cross(F, F1). move([F, W, G, F], [F1, W, G, F1]) :- cross(F, F1). safe([F, W, G, C]) :- F=G, !; F=W, F=C. cross(n,s). cross(s,n). %------t1(AnsPath) :- depthFirstSearch(AnsPath). Radek Maˇrík (marikr@felk.cvut.cz) Classical Planning 15. dubna 2013 40 / 71
Planning Methods State Space State-Transition Graph Example [Wic11] Game of Missionaries and Cannibals move 3 cannibals and 3 missionaries across the river Whenever the number of cannibals is higher than the number of missionaries somewhere, the missionaries are cooked and eaten. Radek Maˇrík (marikr@felk.cvut.cz) Classical Planning 15. dubna 2013 42 / 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 and 24: Representation STRIPS Applicability
Page 25 and 26: Representation STRIPS STRIPS: Plann
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: Planning Methods Logics and Searchi
Page 37 and 38: Planning Methods State Space Planni
Page 39 and 40: Planning Methods State Space State-
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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