arXiv:2608. 08407v1 Announce Type: cross Abstract: A bidder can quietly buy a stake in a company before making an offer for it.
Empirical work on algorithmic collusion asks one question of the data: are prices supracompetitive? We show this can be answered "no" by a conspiracy that is nonetheless profitable.
arXiv:2606. 29457v1 Announce Type: new Abstract: When two companies bid to buy the same target, no one knows exactly what the target is worth.
arXiv:2607. 26385v1 Announce Type: cross Abstract: Empirical work on algorithmic collusion asks one question of the data: are prices supracompetitive?
arXiv:2606. 05363v1 Announce Type: cross Abstract: On a platform with many sellers, should a pricing algorithm explicitly model competitors' prices when learning demand?
arXiv:2608. 07538v1 Announce Type: new Abstract: As LLM agents move from decision support to autonomous procurement, firms need to know whether delegated negotiators create value, divide it predictably, and avoid money-losing contracts.
arXiv:2609.36365v1 Announce Type: new Abstract: Can interaction formats and textual scaffolds help large language model (LLM) agents make better decisions, and do better decisions come with better ex...
arXiv:2608. 09586v1 Announce Type: new Abstract: The Independent Chip Model (ICM) converts tournament chips into reference prize equity, and policies are routinely constructed against those values.
arXiv:2510. 14642v2 Announce Type: replace-cross Abstract: In blockchain networks, the strategic ordering of transactions within blocks has emerged as a significant source of profit extraction, known as Maximal Extractable Value (MEV).
arXiv:2604. 15267v2 Announce Type: replace-cross Abstract: It is increasingly important that LLM agents interact effectively and safely with other goal-pursuing agents, yet, recent works report the opposite trend: LLMs with stronger reasoning capabilities behave _less_ cooperatively in mixed-motive games such as the prisoner's dilemma and public goods settings.
arXiv:2608. 14613v1 Announce Type: new Abstract: Modern LLM-agent frameworks increasingly interoperate through standards such as Anthropic's Model Context Protocol (MCP) for agent-to-tool access and Google's Agent2Agent (A2A) protocol for agent delegation and negotiation.
arXiv:2607. 18045v1 Announce Type: new Abstract: Organizations often pool dispersed information into one ranking and then allow many agents to act on that shared view.
Organizations often pool dispersed information into one ranking and then allow many agents to act on that shared view. In a discovery problem, this can improve beliefs while reducing coverage.