Conclusions & Future Work. In this article we have presented a new me- diated team negotiation model for a team as a multi-individual party negotiating with an oppo- nent in the alternating offers protocol. The present model is capable of assuring unanimously accept- able agreements for all of the team members. It takes advantage of the categorization of negotia- tion issues as predictable and compatible, and un- predictable. The former are those issues whose preferential order over issue values is known from the negotiation domain and it is common among team members (e.g., price in a team of buyers), whereas the latter are those issues whose prefer- ential order over issues values is not known in the negotiation domain. In the case of predictable and compatible issues, there is full potential for coop- eration among team members since if one of the team members demands more from the issue, the other team members are also benefited. Our negoti- ation model takes advantage of this property. Dur- ing the pre-negotiation, each team member shares with a team mediator those unpredictable partial offers (i.e., partial offers that have all of the unpre- dictable issues instantiated) that, even if the team demands the most from predictable issues, preclude the agent from achieving its reservation value. A joint list forbidden unpredictable partial offers is constructed by the team mediator from the lists re- ceived from the team members. In the negotiation, the team mediator coordinates a unanimity voting process to decide whether or not to accept offers received from the opponent. As for the mechanism employed to decide on which offer should be sent to the opponent, the team mediator coordinates two processes: a proposing and voting process where each team member suggests an unpredictable par- tial offer not included in the forbidden list followed by a Xxxxx voting on candidates received, and an iterated process where predictable issues are set is- sue per issue attending to the demands of the team members. We have proposed two different types of team members for the current model: a basic team mem- ber that proposes unpredictable partial offers dur- ing the negotiation solely guided by its own utility function, and a Bayesian team member that sug- gests unpredictable partial offers based on the pref- erences of the team and the preferences of the op- ponent. Results have shown that, as long as pref- erential conflict is present in the team, team mem- bers have an incentive to employ the B...
Conclusions & Future Work. In this chapter, we evaluated an infrastructure using xAAL and MQTT (our PRECIOUS home-automation protocols) in order to offer the possibility to use home automation sensors/actuators in PRECIOUS. It offers access to home environment data in order to have a better understanding of the user context, i.e. environmental factors such as thermal comfort, noise and luminosity levels. But, it also gives capabilities for developers of health applications to integrate feedbacks in order to engage users and help them to change their behaviour. Finally, the infrastructure allows the potential to build in persuasive technology. The subjection of the system to the end-users during tests in the Experiment’HAAL living lab allowed a good acceptance of the system. However to get deeper into usability investigation, it would be interesting to setup the system in participants’ own house to provide them with a true long experience of the PRECIOUS system.
