Name
Abstract | ||
|---|---|---|
Many AI applications involve the interaction of multiple autonomous agents, requiring those agents to reason about their own beliefs, as well as those of other agents. However, planning involving nested beliefs is known to be computationally challenging. In this work, we address the task of synthesizing plans that necessitate reasoning about the beliefs of other agents. We plan from the perspective of a single agent with the potential for goals and actions that involve nested beliefs, non-homogeneous agents, co-present observations, and the ability for one agent to reason as if it were another. We formally characterize our notion of planning with nested belief, and subsequently demonstrate how to automatically convert such problems into problems that appeal to classical planning technology. Our approach represents an important first step towards applying the well-established field of automated planning to the challenging task of planning involving nested beliefs of multiple agents. |
Year | Venue | Field |
|---|---|---|
2015 | PROCEEDINGS OF THE TWENTY-NINTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE | Autonomous agent,Appeal,Computer science,Artificial intelligence,Machine learning,Management science,Applications of artificial intelligence |
DocType | Citations | PageRank |
Conference | 18 | 0.82 |
References | Authors | |
18 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian J. Muise | 1 | 176 | 22.68 |
| Vaishak Belle | 2 | 154 | 24.68 |
| Paolo Felli | 3 | 28 | 5.27 |
| Sheila A. Mcilraith | 4 | 4577 | 491.08 |
| Tim Miller | 5 | 196 | 16.45 |
| Adrian R. Pearce | 6 | 301 | 31.88 |
| Liz Sonenberg | 7 | 802 | 119.89 |