Self-mediated exploration in artificial intelligence inspired by cognitive psychology

• URL: http://arxiv.org/abs/2302.06615v1
• Date: Mon, 13 Feb 2023 18:20:44 GMT
• Title: Self-mediated exploration in artificial intelligence inspired by cognitive psychology
• Authors: Gustavo Assun\c{c}\~ao, Miguel Castelo-Branco, Paulo Menezes
• Abstract summary: Exploration of the physical environment is an indispensable precursor to data acquisition and enables knowledge generation via analytical or direct trialing. This work links human behavior and artificial agents to endorse self-development. A study is subsequently designed to mirror previous human trials, which artificial agents are made to undergo repeatedly towards convergence. Results demonstrate causality, learned by the vast majority of agents, between their internal states and exploration to match those reported for human counterparts.
• Score: 1.3351610617039975
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Exploration of the physical environment is an indispensable precursor to data acquisition and enables knowledge generation via analytical or direct trialing. Artificial Intelligence lacks the exploratory capabilities of even the most underdeveloped organisms, hindering its autonomy and adaptability. Supported by cognitive psychology, this works links human behavior and artificial agents to endorse self-development. In accordance with reported data, paradigms of epistemic and achievement emotion are embedded to machine-learning methodology contingent on their impact when decision making. A study is subsequently designed to mirror previous human trials, which artificial agents are made to undergo repeatedly towards convergence. Results demonstrate causality, learned by the vast majority of agents, between their internal states and exploration to match those reported for human counterparts. The ramifications of these findings are pondered for both research into human cognition and betterment of artificial intelligence.

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