In the context of planning and reasoning about actions and change, we call an action reversible when its effects can be reverted by applying other actions, returning to the original state. Renewed interest in this are...
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In the context of planning and reasoning about actions and change, we call an action reversible when its effects can be reverted by applying other actions, returning to the original state. Renewed interest in this area has led to several results in the context of the PDDL language, widely used for describing planning tasks. In this paper, we propose several solutions to the computational problem of deciding the reversibility of an action. In particular, we leverage an existing translation from PDDL to Answer Set programming (ASP), and then use several different encodings to tackle the problem of action reversibility for the STRIPS fragment of PDDL. For these, we use ASP, as well as epistemic logic programming (ELP), an extension of ASP with epistemic operators, and compare and contrast their strengths and weaknesses.
If we view an ordinary logic program as a set of beliefs of an implicit agent about a world, then a completely epistemiclogical view of logicprogramming would yield a further extension that allows us to reason expli...
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If we view an ordinary logic program as a set of beliefs of an implicit agent about a world, then a completely epistemiclogical view of logicprogramming would yield a further extension that allows us to reason explicitly about beliefs and non-beliefs of any agents. In particular, such a view will accommodate nested beliefs, introspective reasoning of self-beliefs and meta-reasoning of others' beliefs. In this paper, we present the logical foundation of such a view by developing a computational logic of quantified epistemic notions. The semantics of the logic is an extension of Kripke's possible-worlds semantics with variable domains to capture the intensional imputation problem in epistemic notions. A syntactical characterization of this semantics is developed to yield a clausal form of the logic. An efficient resolution mechanisation of this form is described. It is achieved by augmenting Konolige's B-resolution with a semi-set-of-support strategy with linear resolution. Further refinements on a Horn clausal form of the logic with negation as failure are also discussed.
Extending the popular answer set programming paradigm by introspective reasoning capacities has received increasing interest within the last years. Particular attention is given to the formalism of epistemiclogic pro...
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Extending the popular answer set programming paradigm by introspective reasoning capacities has received increasing interest within the last years. Particular attention is given to the formalism of epistemiclogic programs (ELPs) where standard rules are equipped with modal operators which allow to express conditions on literals for being known or possible, that is, contained in all or some answer sets, respectively. ELPs thus deliver multiple collections of answer sets, known as world views. Employing ELPs for reasoning problems so far has mainly been restricted to standard decision problems (complexity analysis) and enumeration (development of systems) of world views. In this paper, we take a next step and contribute to epistemic logic programming in two ways: First, we establish quantitative reasoning for ELPs, where the acceptance of a certain set of literals depends on the number (proportion) of world views that are compatible with the set. Second, we present a novel system that is capable of efficiently solving the underlying counting problems required to answer such quantitative reasoning problems. Our system exploits the graph-based measure treewidth and works by iteratively finding and refining (graph) abstractions of an ELP program. On top of these abstractions, we apply dynamic programming that is combined with utilizing existing search-based solvers like (e)clingo for hard combinatorial subproblems that appear during solving. It turns out that our approach is competitive with existing systems that were introduced recently.
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