What decision theory provides the best procedure for identifying the best action available to a given artificially intelligent system?

Dissertation, University of Oxford (2018)
Download Edit this record How to cite View on PhilPapers
Abstract
Decision theory has had a long-standing history in the behavioural and social sciences as a tool for constructing good approximations of human behaviour. Yet as artificially intelligent systems (AIs) grow in intellectual capacity and eventually outpace humans, decision theory becomes evermore important as a model of AI behaviour. What sort of decision procedure might an AI employ? In this work, I propose that policy-based causal decision theory (PCDT), which places a primacy on the decision-relevance of predictors and simulations of agent behaviour, may be such a procedure. I compare this account to the recently-developed functional decision theory (FDT), which is motivated by similar concerns. I also address potentially counterintuitive features of PCDT, such as its refusal to condition on observations made at certain times.
Categories
PhilPapers/Archive ID
BARWDT-3
Revision history
Archival date: 2018-05-18
View upload history
References found in this work BETA

No references found.

Add more references

Citations of this work BETA

No citations found.

Add more citations

Added to PP index
2018-05-18

Total views
131 ( #19,970 of 39,700 )

Recent downloads (6 months)
53 ( #8,838 of 39,700 )

How can I increase my downloads?

Downloads since first upload
This graph includes both downloads from PhilArchive and clicks to external links.