Semantical considerations on nonmonotonic logic
Artificial Intelligence
Applications of circumscription to formalizing common-sense knowledge
Artificial Intelligence
An experimental logic based on the fundamental deduction principle
Artificial Intelligence
A commonsense theory of nonmonotonic reasoning
Proc. of the 8th international conference on Automated deduction
Introduction to mathematical logic (3rd ed.)
Introduction to mathematical logic (3rd ed.)
Planning for conjunctive goals
Artificial Intelligence
Readings in nonmonotonic reasoning
On formalizing commonsense reasoning using the modal situation logic and reflective reasoning
On formalizing commonsense reasoning using the modal situation logic and reflective reasoning
Planning with constraints
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Classical planners are deficient in dealing with incomplete knowledge, resulting in incorrect interpretation of situations. This paper introduces a new planner ACP that tackles the problem by combining an action model based on Brown's quantified modal logic Z and a bi-directional reasoning scheme. The commonsense reasoning is handled by doing case analysis on default formulas that characterize each action's logical meaning. ACP suggests a simple and efficient approach for maintaining and updating consistent beliefs at major action steps. The frame problem and the qualification problem are dealt by introducing appropriate default rules and consistency criterion to the action model. Incremental constraints are used to ensure that the next state will be consistent with achieving the goals. The whole planning process can be modified when an unexpected action outcome occurs. The research also shows that if a plan is logically possible, ACP will find it. Therefore, ACP is complete.