Social-based planning model for multiagent systems Sara Rodríguez b,⇑ , Yanira de Paz b , Javier Bajo a , Juan M. Corchado b a Escuela Universitaria de Informática, Universidad Pontificia de Salamanca, Compañía 5, 37002 Salamanca, Spain b Departamento Informática y Automática, Universidad de Salamanca, Plaza de la Merced s/n, 37008 Salamanca, Spain article info Keywords: Multi-agent systems Virtual organizations Dynamic architectures Adaptive environments abstract An idea that seems to be gaining considerable ground is that modeling the interactions of a multi-agent system cannot be related exclusively to the actual agent and its communication capabilities, but must involve the use of concepts found in organizational engineering as well. It is possible to establish different types of agent organizations according to the type of communication, the coordination among agents, and the type of agents that comprise the group. Each organization needs to be supported by a coordinated effort that explicitly determines how the agents should be organized and carry out the actions and tasks assigned to them. This research presents a new global coordination model for an agent organization. The primary novelty of the model consists of the dynamic and adaptive planning capability to distribute tasks among the agent members of the organization as effectively as possible. This model is unique in its con- ception, allowing an organization in a highly dynamic environment to employ self-adaptive capabilities in execution time. This allows for the behavior of an agent to be determined by the goals it wishes to reach, while still giving consideration to the goals of other agents and any changes in the environment. The model is evaluated in a multi-agent system developed within an architecture oriented toward THO- MAS organizations and simulated in a virtual environment. Ó 2011 Elsevier Ltd. All rights reserved. 1. Introduction Services based on new technologies are generating new lines of investigation with respect to improving the interactive experience; eliminating any irrelevant services, or those that hold little or no interest, and adapting to the true needs of each user. One of the pri- mary tendencies in a tourist setting is to implement systems to help tourists plan their routes. Recommendation and guidance sys- tems are an attempt to mathematically model and technically emulate the real world recommendation process. These are recog- nized Artificial Intelligence techniques based on software compo- nents that are typical in e-commerce and tourist systems. CBCF (Content-Boosted Collaborative Filtering) (Melville, Mooney, & Nagarajan, 2002), LIBRA (Learning Intelligent Book Recommending Agent) (Mooney & Roy, 2000), MRS (Music Recommendation System) (Hung-Chen & Arbee, 2005), or TIP (Tourist Information Provider) (Hinze, Malik, & Malik, 2005; Hinze & Voisard, 2003) are some examples. MAS (multi-agent systems) stand out among the different AI techniques currently employed, having been used successfully in these types of applications (Bajo et al., 2009; Fonseca, Griss, & Letsinger, 2001; Kowalczyk, Ulieru, & Unland, 2002). Because of their particular characteristics, including autonomy, flexibility and the ability to cooperate, they are perfectly suited for dynamic environments such as these. The current trend with MAS systems is to employ organizational concepts in their design, which helps to focus their work in the field of tourism, since they establish a connection between a tourist organization and an organization at the software agent level with regards to structure, functionality, etc. Virtual organizations (Ferber, Gutknecht, & Michel, 2004) are a means of understanding system models from a sociological per- spective, which is closely related to the area in question. From a business perspective, a virtual organization model is based on the principles of cooperation among businesses within a shared network, and exploits the distinguishing elements that provide the flexibility and quick response capability that form the strategy aimed at customer satisfaction (Schertler, 1998). It is therefore in the best interest of tourist agencies to begin taking into consider- ation this type of organization, which takes advantage of the effi- ciency of new information and communication technologies, to improve their competitiveness among other agencies. Even so, within the development of organizations, both at the business and agent level, we find a set of requirements (Rodríguez, Pérez-Lancho, De Paz, Bajo, & Corchado, 2009) that call for the use of new social models in which the use of open (Zambonelli, Jennings, & Wooldridge, 2003) and adaptive (Di Marzo, Gleizes, & Karageorgos, 2004) systems is possible. Open systems are characterized by the heterogeneous quality of their participants, 0957-4174/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.eswa.2011.04.101 ⇑ Corresponding author. E-mail addresses: srg@usal.es (S. Rodríguez), yanira@usal.es (Y.de Paz), jbajope@ upsa.es (J. Bajo), corchado@usal.es (J.M. Corchado). Expert Systems with Applications 38 (2011) 13005–13023 Contents lists available at ScienceDirect Expert Systems with Applications journal homepage: www.elsevier.com/locate/eswa