Abstract
The BDI architecture, where agents are modelled based on their beliefs, desires, and intentions, provides a practical approach to
developing intelligent agent systems. However, these systems either do not include any capability for first-principles planning (FPP), or they integrate FPP in a rigid and ad-hoc manner that does not define the semantical behaviour. In this paper, we
propose a novel operational semantics for incorporating FPP as an intrinsic planning capability to achieve goals in BDI agent systems. To achieve this, we introduce a declarative goal intention to keep track of declarative goals used by FPP and develop a detailed specification of the appropriate operational behaviour when FPP is pursued, succeeded or failed, suspended, or resumed in the BDI agent systems. Furthermore, we prove that BDI agent systems
and FPP are theoretically compatible for principled integration in both offline and online planning manner. The practical feasibility of this integration is demonstrated, and we show that the resulting agent framework combines the strengths of both BDI agent systems and FPP, thus substantially improving the performance of BDI agent systems when facing unforeseen situations.
developing intelligent agent systems. However, these systems either do not include any capability for first-principles planning (FPP), or they integrate FPP in a rigid and ad-hoc manner that does not define the semantical behaviour. In this paper, we
propose a novel operational semantics for incorporating FPP as an intrinsic planning capability to achieve goals in BDI agent systems. To achieve this, we introduce a declarative goal intention to keep track of declarative goals used by FPP and develop a detailed specification of the appropriate operational behaviour when FPP is pursued, succeeded or failed, suspended, or resumed in the BDI agent systems. Furthermore, we prove that BDI agent systems
and FPP are theoretically compatible for principled integration in both offline and online planning manner. The practical feasibility of this integration is demonstrated, and we show that the resulting agent framework combines the strengths of both BDI agent systems and FPP, thus substantially improving the performance of BDI agent systems when facing unforeseen situations.
| Original language | English |
|---|---|
| Title of host publication | Scalable Uncertainty Management |
| Subtitle of host publication | 12th International Conference, SUM 2018, Milan, Italy, October 3-5, 2018, Proceedings |
| Publisher | Springer Nature |
| Pages | 333-347 |
| Number of pages | 15 |
| ISBN (Electronic) | 9783030004613 |
| ISBN (Print) | 9783030004606 |
| DOIs | |
| Publication status | Published - 11 Sept 2018 |
Publication series
| Name | Lecture Notes in Artificial Intelligence |
|---|---|
| Publisher | Springer Nature |
| Volume | 11142 |
| ISSN (Print) | 0302-9743 |