Imagen de Portada

Seldonian Reinforcement Learning for Ad Hoc Teamwork

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zorzi, Edoardo, Castellini, Alberto, Bakopoulos, Leonidas, Chalkiadakis, Georgios, Farinelli, Alessandro
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A Novel Framework for Uncertainty-Driven Adaptive Exploration
por: Bakopoulos, Leonidas, et al.
Publicado: (2025)

Going Beyond Expert Performance via Deep Implicit Imitation Reinforcement Learning
por: Chrysomallis, Iason, et al.
Publicado: (2025)

Symmetry-Breaking Augmentations for Ad Hoc Teamwork
por: Hammond, Ravi, et al.
Publicado: (2024)

Open Ad Hoc Teamwork with Cooperative Game Theory
por: Wang, Jianhong, et al.
Publicado: (2024)

Learning Logic Specifications for Policy Guidance in POMDPs: an Inductive Logic Programming Approach
por: Meli, Daniele, et al.
Publicado: (2024)

PADiff: Predictive and Adaptive Diffusion Policies for Ad Hoc Teamwork
por: Chan, Hohei, et al.
Publicado: (2025)

Imitation Learning in the Deep Learning Era: A Novel Taxonomy and Recent Advances
por: Chrysomallis, Iason, et al.
Publicado: (2025)

Graph Neural Networks, Deep Reinforcement Learning and Probabilistic Topic Modeling for Strategic Multiagent Settings
por: Chalkiadakis, Georgios, et al.
Publicado: (2025)

On Altruism and Spite in Bimatrix Games
por: Fasoulakis, Michail, et al.
Publicado: (2025)

RecBayes: Recurrent Bayesian Ad Hoc Teamwork in Large Partially Observable Domains
por: Ribeiro, João G., et al.
Publicado: (2025)

Sentinel: Multi-Patch Transformer with Temporal and Channel Attention for Time Series Forecasting
por: Villaboni, Davide, et al.
Publicado: (2025)

Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork
por: Wang, Jianhong, et al.
Publicado: (2025)

Value of Information-Enhanced Exploration in Bootstrapped DQN
por: Plataniotis, Stergios, et al.
Publicado: (2025)

Benchmarking the Limits of In-Context Reinforcement Learning for Ad-Hoc Teamwork
por: Jing, Yuheng, et al.
Publicado: (2026)

Aquatic Navigation: A Challenging Benchmark for Deep Reinforcement Learning
por: Corsi, Davide, et al.
Publicado: (2024)

Analyzing Adversarial Inputs in Deep Reinforcement Learning
por: Corsi, Davide, et al.
Publicado: (2024)

Learning Numeracy: Binary Arithmetic with Neural Turing Machines
por: Castellini, Jacopo
Publicado: (2019)

N-Agent Ad Hoc Teamwork
por: Wang, Caroline, et al.
Publicado: (2024)

Grammarization-Based Grasping with Deep Multi-Autoencoder Latent Space Exploration by Reinforcement Learning Agent
por: Askianakis, Leonidas
Publicado: (2024)

Unsupervised Partner Design Enables Robust Ad-hoc Teamwork
por: Ruhdorfer, Constantin, et al.
Publicado: (2025)

A Minimax Approach to Ad Hoc Teamwork
por: Villin, Victor, et al.
Publicado: (2025)

Collaborative Instance Object Navigation: Leveraging Uncertainty-Awareness to Minimize Human-Agent Dialogues
por: Taioli, Francesco, et al.
Publicado: (2024)

Benchmarking Interaction, Beyond Policy: a Reproducible Benchmark for Collaborative Instance Object Navigation
por: Zorzi, Edoardo, et al.
Publicado: (2026)

Koopman-based Prediction of Connectivity for Flying Ad Hoc Networks
por: Krishnan, Sivaram, et al.
Publicado: (2025)

An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing
por: Decke, Jens, et al.
Publicado: (2024)

Generic-to-Specific Reasoning and Learning for Scalable Ad Hoc Teamwork
por: Dodampegama, Hasra, et al.
Publicado: (2025)

Learning Ad Hoc Network Dynamics via Graph-Structured World Models
por: Karacelebi, Can, et al.
Publicado: (2026)

Agent-Based Post-Hoc Correction of Agricultural Yield Forecasts
por: Beddows, Matthew, et al.
Publicado: (2026)

Sequence Modeling for N-Agent Ad Hoc Teamwork
por: Wang, Caroline, et al.
Publicado: (2025)

MUST: Multi-Scale Structural-Temporal Link Prediction Model for UAV Ad Hoc Networks
por: Pu, Cunlai, et al.
Publicado: (2025)

Simple Ingredients for Offline Reinforcement Learning
por: Cetin, Edoardo, et al.
Publicado: (2024)

Optimal Execution with Reinforcement Learning
por: Hafsi, Yadh, et al.
Publicado: (2024)

Improving Generative Ad Text on Facebook using Reinforcement Learning
por: Jiang, Daniel R., et al.
Publicado: (2025)

Search Inspired Exploration in Reinforcement Learning
por: Sotirchos, Georgios, et al.
Publicado: (2026)

Sequential Enumeration in Large Language Models
por: Hou, Kuinan, et al.
Publicado: (2025)

Learning Personalized Ad Impact via Contextual Reinforcement Learning under Delayed Rewards
por: Cheng, Yuwei, et al.
Publicado: (2025)

Density-Ratio Losses for Post-Hoc Learning to Defer
por: Soen, Alexander, et al.
Publicado: (2026)

ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamwork
por: Wang, Caroline, et al.
Publicado: (2025)

Leveraging Large Language Model for Heterogeneous Ad Hoc Teamwork Collaboration
por: Liu, Xinzhu, et al.
Publicado: (2024)

Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents
por: Rahman, Arrasy, et al.
Publicado: (2023)