collaborators

6 papers

cs.CY2026

A Method for Learning Value Systems in Generative AI

Andrés Holgado-Sánchez, Holger Billhardt, Sascha Ossowski

Value-aware AI systems require explicit computational representations of human values (groundings) and their aggregation into value systems in order to align their decisions with o…

cs.AI2026

Identifying and Understanding Human Values in Text: A Tailorable LLM-based Architecture

Eduardo de la Cruz Fernández, Marcelo Karanik, Sascha Ossowski

As intelligent systems become more autonomous, the scientific community focuses on creating decision-making mechanisms that include ethical and moral considerations, unlike traditi…

cs.AI2026

Learning the Value Systems of Societies with Preference-based Multi-objective Reinforcement Learning

Andrés Holgado-Sánchez, Peter Vamplew, Richard Dazeley +2

Value-aware AI should recognise human values and adapt to the value systems (value-based preferences) of different users. This requires operationalization of values, which can be p…

cs.CY2026

Learning the Value Systems of Agents with Preference-based and Inverse Reinforcement Learning

Andrés Holgado-Sánchez, Holger Billhardt, Alberto Fernández +1

Agreement Technologies refer to open computer systems in which autonomous software agents interact with one another, typically on behalf of humans, in order to come to mutually acc…

cs.CY2025

Value Lens: Using Large Language Models to Understand Human Values

Eduardo de la Cruz Fernández, Marcelo Karanik, Sascha Ossowski

The autonomous decision-making process, which is increasingly applied to computer systems, requires that the choices made by these systems align with human values. In this context,…

cs.AI2025

Learning the Value Systems of Societies from Preferences

Andrés Holgado-Sánchez, Holger Billhardt, Sascha Ossowski +1

Aligning AI systems with human values and the value-based preferences of various stakeholders (their value systems) is key in ethical AI. In value-aware AI systems, decision-making…