Abstract
This paper proposes that we should avoid infinite sets in definitions of AI agent and their environments. For agents that evolve to increase their finite resources it proposes a self-modeling agent definition that avoids assumptions about the agent's future form. And it proposes a consistent and complete logical theory for reasoning by AI agents in our finite universe. © 2014 Springer International Publishing.
Cite
CITATION STYLE
Hibbard, B. (2014). Self-modeling agents evolving in our finite universe. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8598 LNAI, pp. 246–249). Springer Verlag. https://doi.org/10.1007/978-3-319-09274-4_26
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