Sequential Information Design

Sequential information design focuses on strategically revealing information over time to influence a decision-maker's actions, aiming to optimize a sender's objective. Current research employs techniques like transformer-based models and Bayesian optimization, often incorporating reinforcement learning algorithms to learn optimal information release strategies in various settings, including those with unknown parameters. This field is significant for its applications in diverse areas such as drug design, architectural design, and online platform management, offering powerful tools for efficient decision-making and persuasive communication. The development of efficient algorithms for learning optimal information strategies in complex environments remains a key focus.

Papers

October 30, 2023

GPCR-BERT: Interpreting Sequential Design of G Protein Coupled Receptors Using Protein Language Models
Seongwon Kim, Parisa Mollaei, Akshay Antony, Rishikesh Magar, Amir Barati Farimani
BERT Model Protein Sequence Protein Language Model Protein Function Prediction Pre Trained Protein Model Sequence Motif G Protein Coupled Receptor BERT LID Model Sequential Information Design

September 5, 2023

Representation Learning for Sequential Volumetric Design Tasks
Md Ferdous Alam, Yi Wang, Chin-Yi Cheng, Jieliang Luo
Representation Learning Sequential Information Design Volumetric Design

June 25, 2023

Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design
Xubo Yue, Raed Al Kontar, Albert S. Berahas, Yang Liu, Blake N. Johnson
Bayesian Optimization Consensus Group Decision Optimal Design Collaborative Sensing Sequential Information Design

September 8, 2022

Sequential Information Design: Learning to Persuade in the Dark
Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti, Francesco Trovo
Bandit Feedback O$ Regret Sequential Decision Making Persuasive Argument Persuasive Capability Efficient Realization Sequential Information Design

February 22, 2022

Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning
Jibang Wu, Zixuan Zhang, Zhe Feng, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan, Haifeng Xu
Efficient Reinforcement Learning Finite Horizon Bayesian Persuasion Sequential Information Design

Sequential Information Design

Papers

GPCR-BERT: Interpreting Sequential Design of G Protein Coupled Receptors Using Protein Language Models

Representation Learning for Sequential Volumetric Design Tasks

Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design

Sequential Information Design: Learning to Persuade in the Dark

Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning