Abstract
To provide recommendations to groups of tourists is a very complex task, especially due to conflicting preferences and the group’s heterogeneity. The introduction of Multi-Agent Systems (MAS) can be the leverage we are looking for. Their autonomy, isolated state, distribution, and loose coupling make them suitable for the development of distributed systems, being the concept similar to a Microservices architecture. This connection brought a new approach, the Multi-Agent Microservices (MAMS) architecture, which exposes agents as resources through REST endpoints, changing the way MAS are seen and implemented, facilitating the user ↔ agent interaction, with a more efficient interoperability, bringing faster and more intelligent systems. In this demonstration, we propose the use of a MAMS architecture to represent the tourists in a mobile Group Recommender System for Tourism prototype, Grouplanner, exposing their agents and knowledge as resources that can be consumed by HTTP clients by directly communicating with the tourists’ agents using REST endpoints, in order to provide faster and better recommendations.
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Notes
- 1.
To facilitate the demonstration, we are not considering the tourists’ demographic data, motivations, nor travel-related preferences and concerns.
- 2.
This division is also based on the “Personality vs Tourist Attractions Preference” model proposed in our previous work [8].
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Alves, P., Gomes, D., Rodrigues, C., Carneiro, J., Novais, P., Marreiros, G. (2022). Grouplanner: A Group Recommender System for Tourism with Multi-agent MicroServices. In: Dignum, F., Mathieu, P., Corchado, J.M., De La Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Complex Systems Simulation. The PAAMS Collection. PAAMS 2022. Lecture Notes in Computer Science(), vol 13616. Springer, Cham. https://doi.org/10.1007/978-3-031-18192-4_37
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