Computer Games are interesting test beds for research in Artificial Intelligence and Machine Learning. Games usually have continuous state spaces, large action spaces and are characterized by complex relationships between components. Without applying abstraction and generalizations, learning in computer games domain becomes infeasible. Through this work, we investigate some designs that facilit...

every firm learns through firm specific methods. this learning process is operationalized by firm’s knowledge management practices. therefore, knowledge to result in successful learning should be assisted by a combinative framework which can enhance a firms’ absorptive capability. this in turn will play a decisive role for achieving competitive advantage. current literature in strategic managem...

conclusions according to the results, male students preferred to use the kinesthetic learning style more than females, while, female students preferred the aural learning style. knowledge about the learning styles of students at educational institutes is valuable and helps solve learning problems among students, and allows students to become better learners. results out of 184 participants who ...

Reinforcement Learning (RL) has shown promising performance in environments for both robotic control and strategic decision making. However, they are usually treated as separate problems with different objectives. In this work, we propose the use of to solve one, a multi-agent soccer environment. We IEEE Very Small Size Soccer (VSSS) challenge from Latin American Robotics Competition (LARC) stu...