ATSIS: Achieving the Ad hoc Teamwork by Sub-task Inference and Selection
Authors: Shuo Chen, Ewa Andrejczuk, Athirai A. Irissappane, Jie Zhang
IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experiments show the benefits of ATSIS for robust teamwork. In this section, we present the details of the experiments that we conducted to evaluate our algorithm. |
| Researcher Affiliation | Collaboration | Shuo Chen1,2 , Ewa Andrejczuk2 , Athirai A. Irissappane3 and Jie Zhang1 1School of Computer Science and Engineering, Nanyang Technological University 2ST Engineering NTU Corporate Laboratory, Nanyang Technological University 3School of Engineering and Technology, University of Washington |
| Pseudocode | No | The paper describes the ATSIS algorithm in detail using prose and mathematical equations in Section 3, but it does not include a formal pseudocode block or an explicitly labeled algorithm section. |
| Open Source Code | No | The paper does not provide any statement about releasing source code or include a link to a code repository for the methodology described. |
| Open Datasets | No | The paper describes the 'pursuit domain' as the experimental environment and references [Barrett et al., 2017] for context. However, it does not provide concrete access information (link, DOI, repository, or explicit citation for a public dataset) for the data used in the experiments. The pursuit domain appears to be a simulation environment rather than a fixed dataset. |
| Dataset Splits | No | The paper operates within a simulation environment (pursuit domain) and describes simulation parameters (e.g., '1000 UCT simulations', 'maximum depth as 100'). It does not specify training, validation, or test dataset splits in terms of percentages or sample counts, as it's not a static dataset-based experiment in that sense. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., CPU, GPU models, memory, or cloud instance types) used to run the experiments. |
| Software Dependencies | No | The paper mentions the use of 'online POMDP solver DESPOT' and 'UCT' but does not specify version numbers for these or any other software components, libraries, or programming environments used for the experiments. |
| Experiment Setup | Yes | Table 1: Experiment parameters includes 'Simulation 1000 Depth 100 c 0.5 µ 0.95 η 1 r1 30 r2 4 TR1 1 TR2 1'. Additionally, the text states 'In every step, we run at most 1000 UCT simulations with the maximum depth as 100. We set the decision time limit for each step as one second because the task is time sensitive.' |