Empathic Agents: A Hybrid Normative/Consequentialistic Approach

Complex information systems operate with increasing degrees of autonomy. Consequently, such systems should not only optimize for simple metrics (like clicks and views) that reflect the system provider's preferences but also consider norms or rules, as well as the preferences of other agents that are affected by the systems' actions. As a means to achieve such behavior, we propose the design and development of empathic agents that use a mixed rule/utilitybased approach when deciding on how to act, considering both their own and others' utility functions. The agents make use of formal argumentation to reach an agreement on how to act in case of inconsistent beliefs. A promising domain for applying our empathic agents is recommender systems.