A commonsense language for reasoning about causation and rational action
by Ortiz, Charles L.
Artificial Intelligence, vol. 111, no. 2, pp. 73-13-, 1999.
Commonsense causal discourse requires a language with which to express varying degrees of causal connectedness. This paper presents a commonsense language for reasoning about action and causation whose semantics is expressed by way of counterfactuals. Causal relations are analyzed along several dimensions including notions of resource consumption, degree of responsibility, instrumentality, and degree of causal contribution. Grounding the semantics in a level of counterfactual reasoning is shown to play an important role in constraining the set of allowable event descriptions instantiating reports expressed by any of the relations in the language. These ideas are also applied to a causal analysis of rational action: by adopting an explanatory stance, one can characterize action through descriptions that refer to causal connections between mental states and actions. Such a causal analysis resolves some well-known difficulties in correctly ascribing agency and intentionality. Finally, an implementation is described — used to motivate and refine the theory — in which queries involving causal relations between the activities of agents engaged in purposeful behavior within a microworld can be posed.
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Ortiz, Charles L | Program Director |  |
