Conference paper Open Access
Aplib: An Agent Programming Library for Testing Games
Prasetya, Wishnu;
Dastani, Mehdi
Testing modern computer games is notoriously hard. Highly dynamic behavior, inherent non-determinism, and fine grained inter activity blow up their state space; too large for traditional auto- mated testing techniques. An agent-based testing approach offers an alternative as agents’ goal driven planning, adaptivity, and reasoning ability can provide an extra edge. This paper provides a summary of aplib, a Java library for programming intelligent test agents, featuring tactical programming as an abstract way to exert control on agents’ underlying reasoning based behavior. Aplib is implemented in such a way to provide the fluency of a Domain Specific Language (DSL) while still staying in Java, and hence aplib programmers will keep all the advantages that Java programmers get: rich language features and a whole array of development tools.
| Name | Size | |
|---|---|---|
|
aplib_AAMAS_2020_paper.pdf
md5:74ac795e72072d8e0a4605ca91aaafdb |
2.8 MB | Download |
| All versions | This version | |
|---|---|---|
| Views | 25 | 25 |
| Downloads | 12 | 12 |
| Data volume | 33.8 MB | 33.8 MB |
| Unique views | 19 | 19 |
| Unique downloads | 10 | 10 |
- Publication date:
- November 2, 2020
- DOI:
-
- Keyword(s):
- automated game testing AI for automated testing intelligent agents for testing agents tactical programming
- Meeting:
- International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Auckland, New Zealand, 9-13 May, 2020
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International