Title
Autobiography Based Prediction In A Situated Agi Agent
Keywords
Narratives; Prediction; Situated agent
Abstract
The ability to predict the unfolding of future events is an important feature of any situated AGI system. The most widely used approach is to create a model of the world, initialize it with the desired start state and use it to simulate possible future scenarios. In this paper we propose an alternative approach where there is no explicit model building involved. The agent memorizes its personal autobiography in an unprocessed narrative form. When a prediction is needed, the agent aligns story-lines from the autobiography with the current story, extends them into the future, then interprets them in the terms of the current events. We describe the implementation of this approach in the Xapagy cognitive architecture and present some experiments illustrating its operation. © 2014 Springer International Publishing.
Publication Date
1-1-2014
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
8598 LNAI
Number of Pages
11-20
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/978-3-319-09274-4_2
Copyright Status
Unknown
Socpus ID
84905827163 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84905827163
STARS Citation
Bölöni, Ladislau, "Autobiography Based Prediction In A Situated Agi Agent" (2014). Scopus Export 2010-2014. 9237.
https://stars.library.ucf.edu/scopus2010/9237