Representing defeasibility is an important issue in common sense reasoning. In reasoning about action and change, this issue becomes more difficult because domain and action related defeasible information may conflict with general inertia rules. Furthermore, different types of defeasible information may also interfere with each other during the reasoning. In this paper, we develop a prioritized logic programming approach to handle defeasibilities in reasoning about action. In particular, we propose three action languages AT ^ 0 , AT ^ 1 and AT ^ 2 which handle three types of defeasibilities in action domains named defeasible constraints, defeasible observations and actions with defeasible and abnormal effects respectively. Each language with a higher superscript can be viewed as an extension of the language with a lower superscript. These action languages inherit the simple syntax of A language but their semantics is developed in terms of transition systems where transition functions are defined based on prioritized logic programs. By illustrating various examples, we show that our approach eventually provides a powerful mechanism to handle various defeasibilities in temporal prediction and postdiction. We also investigate semantic properties of these three action languages and characterize classes of action domains that present more desirable solutions in reasoning about action within the underlying action languages.
Although the work presented in @cite_2 provided a natural way to represent causality in reasoning about action, there were several restrictions in this action theory. First, due to technical restrictions, only normal defaults or defaults without justifications are the suitable forms to represent causal rules in problem domains. Second, this action theory did not handle the other two major defeasibilities - defeasible observations and actions with defeasible and abnormal effects.
@cite_2
2017479918
Recent research on reasoning about action has shown that the traditional logic form of domain constraints is problematic to represent ramifications of actions that are related to causality of domains. To handle this problem properly, as proposed by some researchers, it is necessary to describe causal relations of domains explicitly in action theories. In this paper, we address this problem from a new point of view. Specifically, unlike other researchers viewing causal relations as some kind of inference rules, we distinguish causal relations between defeasible and non-defeasible cases. It turns out that a causal theory in our formalism can be specified by using Reiter's default logic. Based on this idea, we propose a causality-based minimal change approach for representing effects of actions, and argue that our approach provides more plausible solutions for the ramification and qualification problems compared with other related work. We also describe a logic programming approximation to compute causal theories of actions which provides an implementational basis for our approach. We present here a knowledge representation language, where defeasible and non-defeasible rules can be expressed. The language has two different negations: classical negation, which is represented by the symbol “∼” used for representing contradictory knowledge; and negation as failure, represented by the symbol “not” used for representing incomplete information. Defeasible reasoning is done using a argumentation formalism. Thus, systems for acting in a dynamic domain, that properly handle contradictory and or incomplete information can be developed with this language. An argument is used as a defeasible reason for supporting conclusions. A conclusion q will be considered justified only when the argument that supports it becomes a justification. Building a justification involves the construction of a nondefeated argument A for q. In order to establish that A is a non-defeated argument, the system looks for counterarguments that could be defeaters for A. Since defeaters are arguments, there may exist defeaters for the defeaters, and so on, thus requiring a complete dialectical analysis. The system also detects, avoids, circular argumentation. The language was implemented using an abstract machine defined and developed as an extension of the Warren Abstract Machine (wam). The work reported here introduces Defeasible Logic Programming (DeLP), a formalism that combines results of Logic Programming and Defeasible Argumentation. DeLP provides the possibility of representing information in the form of weak rules in a declarative manner, and a defeasible argumentation inference mechanism for warranting the entailed conclusions. In DeLP an argumentation formalism will be used for deciding between contradictory goals. Queries will be supported by arguments that could be defeated by other arguments. A query @math will succeed when there is an argument @math for @math that is warranted, i.e. the argument @math that supports @math is found undefeated by a warrant procedure that implements a dialectical analysis. The defeasible argumentation basis of DeLP allows to build applications that deal with incomplete and contradictory information in dynamic domains. Thus, the resulting approach is suitable for representing agent's knowledge and for providing an argumentation based reasoning mechanism to agents. In this dissertation I present a formal approach to defeasible reasoning. This mathematical approach is based on the notion of specificity introduced by Poole and the general theory of warrant as presented by Pollock. General background information on the subject of Nonmonotonic Reasoning is presented and some of the shortcomings of existing systems are analyzed. We believe that the approach presented here represents a definite improvement over past systems. The main contribution of this thesis is a formally precise, elegant, clean, well-defined system which exhibits a correct behavior when applied to the benchmark examples in the literature. Model-theoretic semantical issues have been addressed. The investigation on the theoretical issues has aided the study of how this kind of reasoner can be realized on a computer. An interpreter of a restricted language, an extension of Horn clauses with defeasible rules, has been implemented. Finally, the implementation details are discussed.