Solving Multiagent Planning Problems with Concurrent Conditional Effects
Authors: Daniel Furelos-Blanco, Anders Jonsson7594-7601
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Empirically, we show that our compilation can solve challenging multiagent planning problems that require concurrent actions. and We show that our planner is sound and complete, and perform experiments in several concurrent multiagent planning domains to evaluate its performance. |
| Researcher Affiliation | Academia | Daniel Furelos-Blanco Department of Computing Imperial College London London, SW7 2AZ, United Kingdom d.furelos-blanco18@imperial.ac.uk and Anders Jonsson Dept. Information and Communication Technologies Universitat Pompeu Fabra Roc Boronat 138, 08018 Barcelona, Spain anders.jonsson@upf.edu |
| Pseudocode | No | The paper describes the compilation approach and action definitions in text and PDDL-like examples (Figure 1), but does not provide a structured pseudocode or algorithm block for the overall method. |
| Open Source Code | Yes | The code of the compilation and the domains are available at https://github.com/aig-upf/universal-pddl-parser-multiagent. |
| Open Datasets | Yes | We tested our compilations in four concurrent domains: TABLEMOVER, MAZE, WORKSHOP and BOXPUSHING. [...] The MAZE domain (Crosby 2014) [...] The BOXPUSHING domain (Brafman and Zoran 2014) [...] We illustrate this idea using the TABLEMOVER domain (Boutilier and Brafman 2001). |
| Dataset Splits | No | The paper refers to testing its compilations on different 'instances' within domains like TABLEMOVER and MAZE, and mentions variations in joint action size. However, it does not specify explicit training, validation, or test dataset splits in the conventional sense of machine learning, as it is solving planning problems rather than training a model on a dataset. |
| Hardware Specification | Yes | All experiments ran on Intel Xeon E5-2673 v4 @ 2.3GHz processors, with a time limit of 30 minutes and a memory limit of 8 GB. |
| Software Dependencies | No | The paper states: 'The resulting classical planning problems were solved using Fast Downward (Helmert 2006) in the LAMA setting (Richter and Westphal 2010).' However, it does not provide specific version numbers for Fast Downward or LAMA, only citations to their original papers. |
| Experiment Setup | Yes | In each domain, we used three variants of our compilations: unbounded joint action size, and joint action size bounded by C = 2 and C = 4. In all variants, we used the extension that identiļ¬es negative concurrency constraints in the selection phase. |