mlsanityData to 14 Oct 2026

Personality-Driven Decision-Making in LLM-Based Autonomous Agents

arXiv 2504.00727 ↗First posted 1 Apr 2025cs.AI cs.MAcited by 13

On the map: LLM agents and tool use → Social simulation and multi-agent debate

Abstract (arXiv)

The embedding of Large Language Models (LLMs) into autonomous agents is a rapidly developing field which enables dynamic, configurable behaviours without the need for extensive domain-specific training. In our previous work, we introduced SANDMAN, a Deceptive Agent architecture leveraging the Five-Factor OCEAN personality model, demonstrating that personality induction significantly influences agent task planning. Building on these findings, this study presents a novel method for measuring and evaluating how induced personality traits affect task selection processes - specifically planning, scheduling, and decision-making - in LLM-based agents. Our results reveal distinct task-selection patterns aligned with induced OCEAN attributes, underscoring the feasibility of designing highly plausible Deceptive Agents for proactive cyber defense strategies.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 11 of its 48 references that are in the map. First posted on arXiv 1 Apr 2025.

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11 of 48 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023Generative Agents: Interactive Simulacra of Human Behavior7 Apr

Other references · 10

  1. 2017Attention Is All You Needcited by 60,361
  2. 2017Proximal Policy Optimization Algorithmscited by 15,215
  3. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  4. 2015Continuous control with deep reinforcement learningcited by 3,407
  5. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,242
  6. 2022Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studiescited by 515
  7. 2022Using cognitive psychology to understand GPT-3cited by 398
  8. 2022Social Simulacra: Creating Populated Prototypes for Social Computing Systemscited by 301
  9. 2022Language models show human-like content effects on reasoning taskscited by 173
  10. 2017A Game-Theoretic Taxonomy and Survey of Defensive Deception for Cybersecurity and Privacycited by 22

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Citing papers per year: 2025: 6; 2026: 7.

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  1. 2025Inducing Personality in LLM-Based Honeypot Agents: Measuring the Effect on Human-Like Agenda Generation
  2. 2025Identifying Cooperative Personalities in Multi-agent Contexts through Personality Steering with Representation Engineering
  3. 2026On the Behavioral Traits of LLM Agents
  4. 2025Psychologically Enhanced AI Agents
  5. 2025The Power of Personality: A Human Simulation Perspective to Investigate Large Language Model Agents
  6. 2025Can LLMs Generate Behaviors for Embodied Virtual Agents Based on Personality Traits?
  7. 2025Personality as a Probe for LLM Evaluation: Method Trade-offs and Downstream Effects
  8. 2026From Biased Chatbots to Biased Agents: Examining Role Assignment Effects on LLM Agent Robustness