No Pizza for You: Value-based Plan Selection in BDI Agents
Authors: Stephen Cranefield, Michael Winikoff, Virginia Dignum, Frank Dignum
IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The internal representation of the problem has 194 variables and 370 constraints. In a situation where all four values (desire, health, wealth and sustainability) have equal salience, their targets are all 100, and their Value States are (110, 50, 80, 20), the best choice (found by the constraint solver in a fraction of a second7), is to get and eat pizza from the local provider. |
| Researcher Affiliation | Academia | Stephen Cranefield University of Otago stephen.cranefield @otago.ac.nz Michael Winikoff University of Otago michael.winikoff @otago.ac.nz Virginia Dignum TU Delft M.V.Dignum@tudelft.nl Frank Dignum Utrecht University F.P.M.Dignum@uu.nl |
| Pseudocode | No | The paper provides descriptions of the mechanism and a goal-plan tree figure, but no explicitly labeled pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any explicit statement or link regarding the availability of its source code. |
| Open Datasets | No | The paper uses a conceptual 'scenario' for demonstration and evaluation, not a publicly available dataset with specific access information. |
| Dataset Splits | No | The paper uses a conceptual scenario for demonstration and evaluation. It does not mention training, validation, or test dataset splits. |
| Hardware Specification | Yes | 0.2324 seconds, obtained from YALMIPs solvertime property and averaged over 10 runs on a 2.6GHz Intel Core i7 running Windows 7. |
| Software Dependencies | No | The goal-plan tree in Figure 3 has been encoded and our implementation of the mapping in Section 5.1 has been used to generate constraints in MATLAB using the YALMIP (yalmip.github.io) optimisation library. We use MOSEK (mosek.com), a state-of-the-art industrial optimiser, as the underlying solver. No specific version numbers for MATLAB, YALMIP, or MOSEK are provided. |
| Experiment Setup | Yes | In a situation where all four values (desire, health, wealth and sustainability) have equal salience, their targets are all 100, and their Value States are (110, 50, 80, 20), the best choice (found by the constraint solver in a fraction of a second7), is to get and eat pizza from the local provider. |