Name
Abstract | ||
|---|---|---|
Many approaches to BDI agent modeling permit the agent developers to interweave the levels of plans and goals. This is possible through the adoption of new goals inside plans. These goals will have plans of their own, and the definition can extend on many levels. From a software development point of view, the resulting complexity can render the agents' behavior difficult to trace, due to the combination of elements from different abstraction levels, i.e., actions and goal adoptions. This has a negative effect on the development process when designing and debugging agents. In this paper we propose a change of approach that aims to provide a more comprehensible agent model with benefits for the ease of engineering and the fault tolerance of agent systems. This is achieved by imposing a clear separation between the reasoning and the acting levels of the agent. The use of goal adoptions and actions on the environment inside the same plan is therefore forbidden. The approach is illustrated using two theoretical scenarios as well as an agent-based maritime patrol application. We argue that by constraining the agent model we gain in clarity and traceability therefore benefiting the development process and encouraging the adoption of agent-based techniques in industrial contexts. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-14484-9_2 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
goal directed agents,goal reasoning,goal-plan tree | Abstraction,CLARITY,Software engineering,Knowledge management,Fault tolerance,Goal reasoning,Engineering,Belief–desire–intention software model,Software development,Traceability,Debugging | Conference |
Volume | ISSN | Citations |
8758 | 0302-9743 | 3 |
PageRank | References | Authors |
0.49 | 21 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Costin Caval | 1 | 3 | 0.49 |
| Amal El Fallah-Seghrouchni | 2 | 443 | 53.60 |
| Patrick Taillibert | 3 | 77 | 15.76 |