Lion Schulz
Biographic Data
| ID | 3863967 |
|---|---|
| NAME | Lion Schulz |
| GIVEN NAMES | Lion |
| FAMILY NAME | Schulz |
| SIGNATURE | SCHULZ L |
| AFFILIATIONS | Max Planck Institute for Biological Cybernetics |
| ORCID | 0000-0003-1841-1273 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Playing repeated games with large language models
Large language models (LLMs) are increasingly used in applications where they interact with humans and other agents. We propose to use behavioural game theory to study LLMs' cooperation and coordination behaviour. Here we let different LLMs play finitely repeated 2 × 2 games with each other, with human-like strategies, and actual human players. Our results show that LLMs perform particularly well at self-interested games such as the iterated Pris…
A (Dis-)information Theory of Revealed and Unrevealed Preferences
In complex situations involving communication, agents might attempt to mask their intentions, exploiting Shannon’s theory of information as a theory of misinformation. Here, we introduce and analyze a simple multiagent reinforcement learning task where a buyer sends signals to a seller via its actions, and in which both agents are endowed with a recursive theory of mind. We show that this theory of mind, coupled with pure reward-maximization, giv…
No prominent works on this page.
A (Dis-)information Theory of Revealed and Unrevealed Preferences
In complex situations involving communication, agents might attempt to mask their intentions, exploiting Shannon’s theory of information as a theory of misinformation. Here, we introduce and analyze a simple multiagent reinforcement learning task where a buyer sends signals to a seller via its actions, and in which both agents are endowed with a recursive theory of mind. We show that this theory of mind, coupled with pure reward-maximization, giv…
Playing repeated games with large language models
Large language models (LLMs) are increasingly used in applications where they interact with humans and other agents. We propose to use behavioural game theory to study LLMs' cooperation and coordination behaviour. Here we let different LLMs play finitely repeated 2 × 2 games with each other, with human-like strategies, and actual human players. Our results show that LLMs perform particularly well at self-interested games such as the iterated Pris…
Computer Science (2 works) · Computer security (2 works) · Economics (2 works) · Evolutionary Game Theory and Cooperation (2 works) · Mathematics (2 works) · Psychology (2 works) · Social Psychology (2 works) · Adversary (1 work) · Battle (1 work) · Cognition (1 work)