In this paper, we discuss a computational approach to the cognitive task of social planning. First, we specify a class of planning problems that involve an agent who attempts to achieve its goals by altering other agents' mental states. Next, we describe SFPS, a flexible problem solver that generates social plans of this son, including ones that include deception and reasoning about other agents' beliefs. We report the results for experiments on social scenarios that involve different levels of sophistication and that demonstrate both SFPS's capabilities and the sources of its power. Finally, we discuss how our approach to social planning has been informed by-earlier work in the area and propose directions for additional research on the topic.
CITATION STYLE
Pearce, C., Meadows, B., Langley, P., & Barley, M. (2014). Social planning: Achieving goals by altering others’ mental states. In Proceedings of the National Conference on Artificial Intelligence (Vol. 1, pp. 402–408). AI Access Foundation. https://doi.org/10.1609/aaai.v28i1.8757
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