For many large-scale combinatorial search/optimization problems, meta-heuristic algorithms face noisy objective functions, coupled with computationally expensive evaluation times....
This study proposes a simple computational model of evolutionary learning in organizations informed by genetic algorithms. Agents who interact only with neighboring partners seek ...
Preference elicitation (PE) is an important component of interactive decision support systems that aim to make optimal recommendations to users by actively querying their preferen...
The purpose of the current study was to test whether we could create a system where students can learn by teaching a live machine-learning agent. SimStudent is a computer agent tha...
Noboru Matsuda, Victoria Keiser, Rohan Raizada, Ga...
— In this paper we propose an approach to control design of nonlinear time–delay systems, which is based on the construction of symbolic models, where each symbolic state and e...
Giordano Pola, Pierdomenico Pepe, Maria Domenica D...