---
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id: "ad7831d295079883b327507f7d4db2e26b4d5e7ec0162374c606e930f71215df"
canonical_url: "https://aidr.today/ad7831d2?lang=en"
title: "PsyBer-Agent: A Psychology-Driven User Agent for Recommender Systems"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
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published_at: "2026-10-14T04:00:00.000Z"
category: "Research"
topics: ["agent"]
source_urls: ["https://arxiv.org/abs/2610.13989"]
summary: "PsyBer-Agent is a psychology-driven user simulator for recommender systems that models evolving latent user states such as fatigue, affect, and shifting preferences through its Psy-Engine. The framework calibrates simulated behavior against real interaction logs using Unbalanced Gromov-Wasserstein optimal transport and introduces the WebSim environment and PsyBer Benchmark covering multimodal scenarios and seven recommender backbones."
---

# PsyBer\-Agent: A Psychology\-Driven User Agent for Recommender Systems

> [Open the canonical story](<https://aidr.today/ad7831d2?lang=en>)

**Published:** 2026-10-14T04:00:00.000Z
**Category:** Research
**Topics:** agent

## Summary

PsyBer\-Agent is a psychology\-driven user simulator for recommender systems that models evolving latent user states such as fatigue, affect, and shifting preferences through its Psy\-Engine\. The framework calibrates simulated behavior against real interaction logs using Unbalanced Gromov\-Wasserstein optimal transport and introduces the WebSim environment and PsyBer Benchmark covering multimodal scenarios and seven recommender backbones\.

## Sources

- [Story source](<https://arxiv.org/abs/2610.13989>)