Towards An Affective Intelligent Agent System For Decision-Making On Flexible Transportation

This work analyzes the route time, the service cost, and well-being in flexible passenger transportation. By using affective intelligent agents within an artificial environment, seven different scenarios were defined. To offer a broader view, three profiles of passenger agents were considered in each of the seven previously mentioned scenarios: Student profile, which assesses the cost of the route over other decision criteria; Worker profile, which values the time of the route over other factors; and Tourist profile, which values the well-being derived from the route over other factors. Well-being is understood as the satisfaction perceived by the passenger derived from the transport service. Likewise, the transit through streets with positive or negative memories has a direct effect on the well-being of the passenger agent. Depending on the scenario and the configuration of parameters, the results show that in some cases obtaining higher well-being does not imply a substantially higher cost. Likewise, in some cases, following an option that seeks higher well-being does not substantially represent a longer travel time.