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Deep Learning and Artificial General Intelligence: Still a Long Way to Go
In recent years, deep learning using neural network architecture, i. e. deep neural networks, has been on the frontier of computer science research.
A Crossover That Matches Diverse Parents Together in Evolutionary Algorithms
Crossover and mutation are the two main operators that lead to new solutions in evolutionary approaches.
Monte Carlo Tree Search: A Review of Recent Modifications and Applications
Monte Carlo Tree Search (MCTS) is a powerful approach to designing game-playing bots or solving sequential decision problems.
Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms
We investigate the impact of supervised prediction models on the strength and efficiency of artificial agents that use the Monte-Carlo Tree Search (MCTS) algorithm to play a popular video game Hearthstone: Heroes of Warcraft.
Helping AI to Play Hearthstone: AAIA'17 Data Mining Challenge
This paper summarizes the AAIA'17 Data Mining Challenge: Helping AI to Play Hearthstone which was held between March 23, and May 15, 2017 at the Knowledge Pit platform.
