2022/05/20 by Nadia M. Ady, Roshan Shariff, Ady, Nadia M. +5
Neuroscience · Psychology · Social Sciences · #Experimental Behavioral Economics Studies #FOS: Computer and information sciences #Machine Learning (cs.LG) #Psychological and Educational Research Studies #Psychology of Moral and Emotional Judgment
paper · pdf · doi:10.48550/arxiv.2205.10407
openalex publication_date 2022/05/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Curiosity for machine agents has been a focus of intense research. The study of human and animal curiosity, particularly specific curiosity, has unearthed several properties that would offer important benefits for machine learners, but that have not yet been well-explored in machine intelligence. In this work, we introduce three of the most immediate of these properties -- directedness, cessation when satisfied, and voluntary exposure -- and show how they may be implemented together in a proof-of-concept reinforcement learning agent; further, we demonstrate how the properties manifest in the behaviour of this agent in a simple non-episodic grid-world environment that includes curiosity-inducing locations and induced targets of curiosity. As we would hope, the agent exhibits short-term directed behaviour while updating long-term preferences to adaptively seek out curiosity-inducing situations. This work therefore presents a novel view into how specific curiosity operates and in the future might be integrated into the behaviour of goal-seeking, decision-making agents in complex environments.