Citing recent successes in forecasting elections, movies, products, and other outcomes, prediction market advocates call for widespread use of market-based methods for government ...
Sharad Goel, Daniel M. Reeves, Duncan J. Watts, Da...
Users’ critiques to the current recommendation form a crucial feedback mechanism for refining their preference models and improving a system’s accuracy in recommendations that ...
Agents in a competitive interaction can greatly benefit from adapting to a particular adversary, rather than using the same general strategy against all opponents. One method of s...
Discrete-event network simulation is a major tool for the research and development of mobile ad-hoc networks (MANETs). These simulations are used for debugging, teaching, understa...
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...