Name
Abstract | ||
|---|---|---|
We present a computational model, MoralDM, which integrates several AI techniques in order to model recent psychological findings on moral decision-making. Current theories of moral decision-making extend beyond pure utilitarian models by relying on contextual factors that vary with culture. MoralDM uses a natural language system to produce formal representations from psychological stimuli, to reduce tailorability. The impacts of secular versus sacred values are modeled via qualitative reasoning, using an order of magnitude representation. MoralDM uses a combination of first-principles reasoning and analogical reasoning to determine consequences and utilities when making moral judgments. We describe how MoralDM works and show that it can model psychological results and improve its performance via accumulating examples. |
Year | Venue | Keywords |
|---|---|---|
2008 | AAAI | moral judgment,qualitative reasoning,psychological stimulus,first-principles reasoning,moraldm work,moral decision-making,integrated reasoning approach,computational model,psychological result,analogical reasoning,pure utilitarian model,first principle,natural language,computer model |
Field | DocType | Citations |
Social cognitive theory of morality,Computer science,Model-based reasoning,Cognitive psychology,Analytic reasoning,Deductive reasoning,Artificial intelligence,Reasoning system,Case-based reasoning,Verbal reasoning,Machine learning,Qualitative reasoning | Conference | 21 |
PageRank | References | Authors |
1.39 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Morteza Dehghani | 1 | 60 | 14.38 |
| Emmett Tomai | 2 | 92 | 12.95 |
| Kenneth D. Forbus | 3 | 3131 | 862.14 |
| Matthew Klenk | 4 | 98 | 8.63 |