Name
Abstract | ||
|---|---|---|
In part motivated by topics such as agency safety, there is an increasing interest in goal reasoning, a form of agency where the agents formulate their own goals. One of the crucial aspects of goal reasoning agents is their ability to detect if the execution of their courses of actions meet their own expectations. We present a taxonomy of different forms of expectations as used by goal reasoning agents when monitoring their own execution. We summarize and contrast the current understanding of how to define and check expectations based on different knowledge sources used. We also identify gaps in our understanding of expectations. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1609/aaai.v33i01.33019823 | AAAI |
Field | DocType | Volume |
Computer science,Goal reasoning,Artificial intelligence,Machine learning,Management science | Conference | 33 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hector Muñoz-Avila | 1 | 522 | 44.02 |
| Dustin Dannenhauer | 2 | 16 | 4.55 |
| Noah Reifsnyder | 3 | 0 | 0.34 |