Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Scalable Planning and Learning for Multiagent POMDPs
Authors: Christopher Amato, Frans Oliehoek
AAAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Here, we empirically investigate the effectiveness of our factorization methods by comparing them to non-factored methods in the planning and learning settings. Experimental results show that we are able to provide high quality solutions to large multiagent planning and learning problems. |
| Researcher Affiliation | Academia | Christopher Amato CSAIL, MIT Cambridge, MA 02139 EMAIL Frans A. Oliehoek Informatics Institute, University of Amsterdam Dept. of CS, University of Liverpool EMAIL |
| Pseudocode | No | The paper describes the algorithms conceptually and references modifications to existing functions but does not provide any formal pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not contain any explicit statements about releasing code or links to a code repository. |
| Open Datasets | No | The paper describes custom problem settings ('firefighting problems', 'sensor network problems') used in the experiments but does not provide access information (links, citations) for publicly available datasets. |
| Dataset Splits | No | The paper mentions 'Each experiment was run for a given number of simulations, the number of samples used at each step to choose an action, and averaged over a number of episodes.' but does not specify any training/validation/test dataset splits. |
| Hardware Specification | Yes | Experiments were run on a single core of a 2.5 GHz machine with 8GB of memory. |
| Software Dependencies | No | The paper mentions comparing 'factored representations to the flat version using POMCP' and using 'the same code base', but it does not specify any software names with version numbers. |
| Experiment Setup | Yes | Each experiment was run for a given number of simulations, the number of samples used at each step to choose an action, and averaged over a number of episodes. We report undiscounted return with the standard error. For the BA-MPOMDPs, H = 10, 50. |