To endow computers with common sense is one of the major long-term goals of Artificial Intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic. Commonsense Reasoning is a detailed, high-level reference on logic-based commonsense reasoning. It uses the event calculus, a highly powerful and usable tool for commonsense reasoning, which Erik T. Mueller demonstrates as the most effective tool for the broadest range of applications. He provides an up-to-date work promoting the use of the event calculus for commonsense reasoning, and bringing into one place information scattered across many books and papers. Mueller shares the knowledge gained in using the event calculus and extends the literature with detailed event calculus solutions to problems that span many areas of the commonsense world.
· Covers key areas of commonsense reasoning including action, change, defaults, space, and mental states.
· The first full book on commonsense reasoning to use the event calculus.
· Contextualizes the event calculus within the framework of commonsense reasoning, introducing the event calculus as the best method overall.
· Focuses on how to use the event calculus formalism to perform commonsense reasoning, while existing papers and books examine the formalisms themselves.
· Includes fully worked out proofs and circumscriptions for every example.
· Describes software tools that can be downloaded and used for automated commonsense reasoning, and real-world applications that have been built using the event calculus.
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agent Artificial Intelligence axiomatization binary relation CIRC CIRCLX circumscription classical logic commonsense knowledge commonsense law commonsense reasoning concurrent events conjunction continuous change DEC5 DEC9 default reasoning defined DEFINITION Discrete Event Calculus discussed domain description effect axioms effects of events Event Calculus Reasoner event occurrences event that occurs example first-order logic fluent calculus fluent f follows Formalize formula function symbol goal Happens Happens(e Happens(e,t Holds.At(Believe(a HoldsAt(f,t indirect effects infer Initiates Initiates(e input integer introduced knowledge representation law of inertia Lifschitz McCarthy method Miller and Shanahan Nathan node object occurs at timepoint postdiction predicate symbol problem Proof PROPOSITION qualification problem ramification problem real number Released At(6 ReleasedAt(f,t Releases(e representation Sandewall Satiated(Cat scenario second-order logic Section situation calculus society of mind sort specify temporal Terminates Terminates(e Theorem 2.1 Thielscher ThoughtTreasure timepoint timepoint term trigger axioms truth value variables