Papers
4
Total Citations
89
H-Index
4
About
Samuel Gomes investigates the intersection of social robotics, multi-agent systems, and collective behavior, with a focus on how humans and machines cooperate. His work explores prosociality in human-robot teams, examining how people collaborate with robots in social dilemmas akin to public goods games—a study that has garnered 44 citations and highlights the potential for robots to foster cooperative dynamics. Gomes also delves into the "dark side" of embodiment, comparing interactions with embodied social robots versus disembodied agents (19 citations), revealing how physical presence shapes trust and teamwork. Extending to multi-agent systems, his research on partner selection in collective risk dilemmas (16 and 10 citations) identifies strategies like "picky losers and carefree winners" that sustain cooperation by avoiding free-riders. These contributions advance distributed artificial intelligence and human-robot interaction, offering insights for designing agents that promote collective action. Gomes’s work is notable for bridging experimental psychology and AI, providing empirical evidence on how embodiment and partner choice influence cooperative outcomes in mixed human-robot teams.
Research Focus
Key Achievements
Top Papers
- 1Exploring Prosociality in Human-Robot Teams44 citations · 2019
- 2The Dark Side of Embodiment - Teaming Up With Robots VS Disembodied Agents19 citations · 2020
- 3
- 4Outcome-based Partner Selection in Collective Risk Dilemmas10 citations · 2019