Add to ORKGThis paper explores memory-based approaches to learn-ing games. The learning element stores evaluated posi-tions for future use. A deterministic game (checkers) and a stochastic game (backgammon) are being used as test cases for these approaches.
[[abstract]]For junior high school students, when they exposure to the chemical learning, most stude...
Most games have a set algorithm that does not change. This means that these programs cannot adapt to...
This paper investigates the application of a modified version of the board game of Monopoly to explo...
A promising approach to learn to play board games is to use reinforcement learning algorithms that c...
A promising approach to learn to play board games is to use reinforcement learning algorithms that c...
A promising approach to learn to play board games is to use reinforcement learning algorithms that c...
This paper deals with creating artificial intelligence for computer player for deterministic games s...
AbstractThe memory game, or concentration, as it is sometimes called, is a popular card game played ...
The thesis is dedicated to the study and implementation of methods used for learning from the course...
The memory game, or concentration, as it is sometimes called, is a popular card game played by child...
This research is aimed to describe a learning trajectory for probability through game-based learning...
This paper presents a new, probabilistic model of learning in games. The model is set in the usual r...
The incorporation of learning into commercial games can enrich the player experience, but may concer...
We introduce a two-player model of reinforcement learning with memory. Past actions of an iterated g...
This paper posits the use of computer games as cognitive development tools that can provide players ...
[[abstract]]For junior high school students, when they exposure to the chemical learning, most stude...
Most games have a set algorithm that does not change. This means that these programs cannot adapt to...
This paper investigates the application of a modified version of the board game of Monopoly to explo...
A promising approach to learn to play board games is to use reinforcement learning algorithms that c...
A promising approach to learn to play board games is to use reinforcement learning algorithms that c...
A promising approach to learn to play board games is to use reinforcement learning algorithms that c...
This paper deals with creating artificial intelligence for computer player for deterministic games s...
AbstractThe memory game, or concentration, as it is sometimes called, is a popular card game played ...
The thesis is dedicated to the study and implementation of methods used for learning from the course...
The memory game, or concentration, as it is sometimes called, is a popular card game played by child...
This research is aimed to describe a learning trajectory for probability through game-based learning...
This paper presents a new, probabilistic model of learning in games. The model is set in the usual r...
The incorporation of learning into commercial games can enrich the player experience, but may concer...
We introduce a two-player model of reinforcement learning with memory. Past actions of an iterated g...
This paper posits the use of computer games as cognitive development tools that can provide players ...
[[abstract]]For junior high school students, when they exposure to the chemical learning, most stude...
Most games have a set algorithm that does not change. This means that these programs cannot adapt to...
This paper investigates the application of a modified version of the board game of Monopoly to explo...