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Despite their evolution from early copper-token schemes to sophisticated digital solutions, loyalty programs remain predominantly closed ecosystems, with brands retaining full control over all components. Coalition loyalty programs emerged…
Persistent memory is turning language-model-based agents from stateless participants in isolated interactions into state-bearing components of LLM-based multi-agent systems. As memory becomes durable, reloadable, and behavior-shaping across…
Peer-to-peer trading and the move to decentralized grids have reshaped the energy markets in the United States. Notwithstanding, such developments lead to new challenges, mainly regarding the safety and authenticity of energy trade. This…
In this paper, we make a case that endogenous tokens such as cryptoassets are not money. First, we define and classify tokens found on public, permissionless ledgers, contrasting them with privately issued stablecoins and proposed CBDC…
Organisations are increasingly open to scrutiny, and need to be able to prove that they operate in a fair and ethical way. Accountability should extend to the production and use of the data and knowledge assets used in AI systems, as it…
Existing benchmarks have laid the foundation for travel planning agents by establishing API-centric paradigms. However, as the capabilities of Autonomous Agents continue to advance, their evaluation must evolve beyond simple tool execution…
Memory has emerged, and will continue to remain, a core capability of foundation model-based agents. As research on agent memory rapidly expands and attracts unprecedented attention, the field has also become increasingly fragmented.…
Open banking framework enables third party providers to access financial data across banking institutions, leading to unprecedented innovations in the financial sector. However, some open banking standards remain susceptible to severe…
Prior work on trustworthy AI emphasizes model-internal properties such as bias mitigation, adversarial robustness, and interpretability. As AI systems evolve into autonomous agents deployed in open environments and increasingly connected to…
Conversational agents are increasingly deployed in knowledge-intensive settings, where correct behavior depends on retrieving and applying domain-specific knowledge from large, proprietary, and unstructured corpora during live interactions…
Decentralized trading of real-world alternative assets (e.g., gold) requires bridging physical asset custody with blockchain systems while meeting strict requirements for compliance, liquidity, and risk management. We present GoldMine OS, a…
AI agents integrated with Web3 offer autonomy and openness but raise security concerns as they interact with financial protocols and immutable smart contracts. This paper investigates the vulnerabilities of AI agents within blockchain-based…
Vast quantities of compute (GPU cycles on personal workstations, idle inference servers, and edge devices between jobs) go unused because no incentive-aligned protocol exists for their owners to share them safely and profitably. Existing…
We formalize three design axioms for sustained adoption of agent-centric AI systems executing multi-step tasks: (A1) Reliability > Novelty; (A2) Embed > Destination; (A3) Agency > Chat. We model adoption as a sum of a decaying novelty term…
Agentic analytics is turning the lakehouse into a multi-version system: swarms of (human or AI) producers materialize competing pipelines in data branches, while (human or AI) consumers need answers without knowing the underlying data…
Agent-based models have emerged as a promising paradigm for addressing ever increasing complexity of information systems. In its initial days in the 1990s when object-oriented modeling was at its peak, an agent was treated as a special kind…
AI agents powered by large language models are increasingly deployed as cloud services that autonomously access sensitive data, invoke external tools, and interact with other agents. However, these agents run within a complex multi-party…
The paper presents an advanced version of an adaptive market-making agent capable of performing experiential learning, exploiting a "try and fail" approach relying on a swarm of subordinate agents executed in a virtual environment to…
We study auctions with additive valuations where agents have a limit on the number of goods they may receive. We refer to such valuations as {\em capacitated} and seek mechanisms that maximize social welfare and are simultaneously incentive…
Collusion in market pricing is a concept associated with human actions to raise market prices through artificially limited supply. Recently, the idea of algorithmic collusion was put forward, where the human action in the pricing process is…