Enhancing human-AI collaboration in Opportunistic Software Composition (OCE)

Kévin Delcourt (1) , Sylvie Trouilhet (1) , Jean-Paul Arcangeli (1) , Françoise Adreit (1)

1 IRIT-SMAC - Systèmes Multi-Agents Coopératifs

Our focus is on improving the Opportunistic Composition Engine's (OCE) human-AI interaction. To accomplish this goal, we identify design solutions and explore how they could be applied to AmI and OCE. We have organized this study using the guidelines of Amershi et al., which offer a comprehensive framework for answering all of our research questions. For each guideline, we discuss its significance and how it can enhance human interaction with an IML application like OCE.

Mots clés: Human-AI Interaction; Interactive Machine Learning; Ambient Intelligence; Reinforcement Learning; Software Composition

Domaines: Informatique [cs]; Interface homme-machine [cs.HC]; Informatique ubiquitaire; Apprentissage [cs.LG]; Système multi-agents [cs.MA]

Kévin Delcourt, Sylvie Trouilhet, Jean-Paul Arcangeli, Françoise Adreit. Enhancing human-AI collaboration in Opportunistic Software Composition (OCE). IRIT/RR–2024–01–FR, IRIT : Institut de recherche en informatique de Toulouse. 2024. ⟨hal-04476871⟩