| M. Thielscher. Reasoning about actions: Steady versus stabilizing state constraints. Artifical Intelligence, 104:339-355, 1988. |
....class of planning problems. However, it seems likely that there is a more general way to translate the formulas of a larger fragment of the fluent calculus while keeping the restriction to propositional fluents, such that we could introduce recent work on the fluent calculus like ramification [18, 19] into our planner without modifying the translation and the proofs. The concept of ramification within the fluent calculus involves a limited use of constructs of second order logic, namely a calculation of the transitive closure of a relation over states, but this does not seem to pose a ....
Michael Thielscher. Reasoning about actions: Steady versus stabilizing state constraints. Artificial Intelligence, 104:339--355, 1998.
....class of fluent calculus formulas. It seems likely that there is a more general way to translate the formulas of a larger fragment of the fluent calculus while keeping the restriction to propositional fluents, such that we could introduce recent work on the fluent calculus like ramification [20, 21] into the planner without modifying the translation and the proofs. The concept of ramification within the fluent calculus involves a limited use of constructs of second order logic, namely a calculation of the transitive closure of a relation over states, but this does not seem to pose a ....
Michael Thielscher. Reasoning about actions: Steady versus stabilizing state constraints. Artificial Intelligence, 104:339--355, 1998.
.... (z) P (g z) 8z) P (z) 1 More speci cally, these axioms ensure that in every model M we have that state M with operations ; M and M is isomorphic to the set of nite multisets over fluent M with operations ; and [ denoting the empty multiset and multiset union (St orr Thielscher 2000). 2 Please note that (9g) z = g is true i z is contained in the sort fluent , which is a subsort of the sort state . FS0 contains a single axiom I (state(s 0 ) of the form state(s 0 ) t describing the initial state, where t is a constructor state term. Fms contains an axiom ....
Thielscher, M. 1998b. Reasoning about actions: Steady versus stabilizing state constraints. Articial Intelligence 104:339-355.
....a speci c class of uent calculus formulas. It seems likely that there is a more general way to translate the formulas of a larger fragment of the uent calculus while keeping the restriction to propositional uents, such that we could introduce recent work on the uent calculus like rami cation [17, 18] into the planner without modifying the translation and the proofs. The concept of rami cation within the uent calculus involves a limited use of constructs of second order logic, namely a calculation of the transitive closure of a relation over states, but this does not seem to pose a dicult ....
Michael Thielscher. Reasoning about actions: Steady versus stabilizing state constraints. Articial Intelligence, 104:339-355, 1998.
....soon as it is shot. More precisely, if both Walking(Turkey) and :Dead(Turkey) happen to be true when an action is performed which causes Dead (Turkey) then this action additionally causes :Walking(Turkey) Such further, indirect effects can be accounted for with the help of causal relationships [20, 21]. Each of them defines circumstances under which a single indirect effect is to be expected. A successor state is then the result of applying a chain of causal relationships, after having computed the direct effects of an action. Let Causes(z; e; z 0 ; e 0 ) denote that in the current state z ....
Michael Thielscher. Reasoning about actions: Steady versus stabilizing state constraints. Artificial Intelligence, 104:339--355, 1998.
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Michael Thielscher. Reasoning about actions: Steady versus stabilizing state constraints. Artificial Intelligence, 1998. (To appear).
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M. Thielscher. Reasoning about actions: Steady versus stabilizing state constraints. Artifical Intelligence, 104:339-355, 1988.
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M. Thielscher. Reasoning about actions: Steady versus stabilizing state constraints. Artifical Intelligence, 104:339-355, 1988.
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M. Thielscher. Reasoning about actions: Steady versus stabilizing state constraints. Artifical Intelligence, 104:339ce, 194:
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