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A far-sighted approach to machine learning

A new technique enables artificial intelligence agents to think much farther into the future when considering how their behaviors can influence the behaviors of other AI agents, toward the completion of a task. This approach improves long-term performance of cooperative or competitive AI agents. ....

Richardc Maclaurin , Laboratory For Information , Watson Ai Lab , Quebec Artificial Intelligence Institute , Oxford University , Dong Ki Kim , Decision Systems , Mila Quebec Artificial Intelligence Institute , Neural Information Processing , Jonathanp How , Ultiagent Reinforcement Learning , Reinforcement Learning , Machine Learning , Ptimization Objectives ,

"Review on customized bus route optimization" by Chang Xi Ma, Wei Hao et al.

To comprehensively review the research progress in customized bus route optimization, the relevant literatures were classified and analyzed from three aspects including optimization objective, issue scenario, and solution algorithm. Analysis results show that researches on the single-objective optimization of customized bus routes have mainly focused on the travel time, operating mileage, operating cost, operating revenue, and total system cost formed by the linear weighting of multiple costs. However, research on the multi-objective optimization was mainly achieved by simultaneously considering two or three objectives, including the operating cost, travel cost, and service quality. According to the number of departure and arrival stations, the issue scenarios of customized bus route optimization problems can be divided into three types including one-to-one, many-to-one, and many-to-many. Research on the time impedance scenarios between different stops mainly focuses on the static time ....

Customized Bus , Ssue Scenario , Ptimization Objectives , Route Optimization , Olution Algorithm , Transportation Planning ,