Construal Level Theory for Agent-based Planning

Christopher McClurg, Alan R. Wagner, Sarah Rajtmajer

Research output: Contribution to journalConference articlepeer-review


Construal level theory (CLT) suggests that a person creates abstract mental representations, known as construals, in order to generate predictions, form counterfactuals, and guide behavior with respect to distal times, places, and actions [1]. This paper takes a step towards implementing CLT in agent reasoning; the impact of abstraction level on an ability to scavenge for needed items and ingredients is investigated. Our approach was parametrically tested in a Minecraft environment. Results show that planning with construals increased trial success rate by 14.8% as compared to planning without construals. Our work lays the foundation for a family of cognitively-plausible models that would allow computational agents to generate predictions about future events and valuations of future plans based on very limited prior training.

Original languageEnglish (US)
JournalCEUR Workshop Proceedings
StatePublished - 2022
Event2022 Thinking Fast and Slow and Other Cognitive Theories in AI, a AAAI 2022 Fall Symposium, TFSOCTAI 2022 - Arlington, United States
Duration: Nov 17 2022Nov 19 2022

All Science Journal Classification (ASJC) codes

  • General Computer Science


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