Cooperative Multi-Agent Bandits with Heavy Tails
Authors: Abhimanyu Dubey, Alex ‘Sandy’ Pentland
ICML 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conduct experiments using α-stable densities (L evy, 1925), that admit finite moments only of order < α 2, and we consider α-stable densities where α 1. The α-stable family includes several widely used distributions, such as Gaussian (α = 2, only lighttailed density), L evy (α = 0.5) and Cauchy (α=1). |
| Researcher Affiliation | Academia | 1Media Lab and Institute for Data, Systems and Society, Massachusetts Institute of Technology. Correspondence to: Abhimanyu Dubey <dubeya@mit.edu>. |
| Pseudocode | Yes | Algorithm 1 DECENTRALIZED MP-UCB; Algorithm 2 CENTRALIZED MP-UCB; Algorithm 3 ONLINE TRIMMED MEAN ESTIMATOR |
| Open Source Code | No | The paper does not contain any explicit statements about releasing source code or providing links to code repositories for the described methodology. |
| Open Datasets | Yes | We select the p2p-Gnutella04 (Figure 1C) and ego-Facebook (Figure 1D) network structures from the SNAP repository (Leskovec & Sosiˇc, 2016) to experiment with in the real-world setting. |
| Dataset Splits | No | The paper describes generating random graphs ('Erdos-Renyi (ER) (p = 0.7) and Barabasi-Albert (BA) (m = 5) random graph families') and sampling subgraphs from real-world networks ('subgraphs of 500 nodes'). However, it does not specify any explicit train/validation/test dataset splits or cross-validation setups. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., CPU/GPU models, memory, or cloud instance types) used for running the experiments. |
| Software Dependencies | No | The paper mentions using 'the approximate algorithm presented in (Lucas, 2014) that uses the QUBO (Glover & Kochenberger, 2018) solver' but does not provide specific version numbers for any software dependencies. |
| Experiment Setup | Yes | We set K = 5, α = 1.9 for the standard α-stable density, and sample arm means randomly from the interval [0, 1] for each arm every experiment. We then construct random graphs on 200 agents from the Erdos-Renyi (ER) (p = 0.7) and Barabasi-Albert (BA) (m = 5) random graph families, and compare all three of our algorithms (using the trimmed mean estimator, with γ = diam(G)/2) with the CONSENSUS-UCB and single-agent ROBUST-UCB(Bubeck et al., 2013) algorithms. |