Name
Title | ||
|---|---|---|
Inferring and Conveying Intentionality - Beyond Numerical Rewards to Logical Intentions. |
Abstract | ||
|---|---|---|
Shared intentionality is a critical component in developing conscious AI agents capable of collaboration, self-reflection, deliberation, and reasoning. We formulate inference of shared intentionality as an inverse reinforcement learning problem with logical reward specifications. We show how the approach can infer task descriptions from demonstrations. We also extend our approach to actively convey intentionality. We demonstrate the approach on a simple grid-world example. |
Year | Venue | Field |
|---|---|---|
2019 | AAAI Spring Symposium - Towards Conscious AI Systems | Intentionality,Computer science,Cognitive science,Artificial intelligence,Machine learning |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Susmit Jha | 1 | 460 | 33.61 |
| John Rushby | 2 | 2459 | 235.69 |