An Analysis of the Deliberation and Task Performance of an Active Logic Based Agent (Student Abstract)

AAAI 2023 pp. 16228-16229

doi:10.1609/AAAI.V37I13.26974 /aaai/2023/herron2023aaai-analysis/

Abstract

Active logic is a time-situated reasoner that can track the history of inferences, detect contradictions, and make parallel inferences in time. In this paper, we explore the behavior of an active-logic based agent on different sets of action selection axioms for a time-constrained target search task. We compare the performance of a baseline set of axioms that does not avoid redundant actions with five other axiom sets that avoid repeated actions but vary in their knowledge content. The results of these experiments show the importance of balancing boldness and caution for target search.

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Text

Herron and Josyula. "An Analysis of the Deliberation and Task Performance of an Active Logic Based Agent (Student Abstract)." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I13.26974

Markdown

[Herron and Josyula. "An Analysis of the Deliberation and Task Performance of an Active Logic Based Agent (Student Abstract)." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/herron2023aaai-analysis/) doi:10.1609/AAAI.V37I13.26974

BibTeX

@inproceedings{herron2023aaai-analysis,
  title     = {{An Analysis of the Deliberation and Task Performance of an Active Logic Based Agent (Student Abstract)}},
  author    = {Herron, Anthony and Josyula, Darsana P.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2023},
  pages     = {16228-16229},
  doi       = {10.1609/AAAI.V37I13.26974},
  url       = {https://mlanthology.org/aaai/2023/herron2023aaai-analysis/}
}