A survey of monte carlo tree search methods
Monte Carlo tree search (MCTS) is a recently proposed search method that combines the
precision of tree search with the generality of random sampling. It has received considerable …
precision of tree search with the generality of random sampling. It has received considerable …
Flow network based generative models for non-iterative diverse candidate generation
This paper is about the problem of learning a stochastic policy for generating an object (like
a molecular graph) from a sequence of actions, such that the probability of generating an …
a molecular graph) from a sequence of actions, such that the probability of generating an …
Imagination-augmented agents for deep reinforcement learning
Abstract We introduce Imagination-Augmented Agents (I2As), a novel architecture for deep
reinforcement learning combining model-free and model-based aspects. In contrast to most …
reinforcement learning combining model-free and model-based aspects. In contrast to most …
Robogrammar: graph grammar for terrain-optimized robot design
We present RoboGrammar, a fully automated approach for generating optimized robot
structures to traverse given terrains. In this framework, we represent each robot design as a …
structures to traverse given terrains. In this framework, we represent each robot design as a …
Imagination-augmented agents for deep reinforcement learning
We introduce Imagination-Augmented Agents (I2As), a novel architecture for deep
reinforcement learning combining model-free and model-based aspects. In contrast to most …
reinforcement learning combining model-free and model-based aspects. In contrast to most …
Information set monte carlo tree search
Monte Carlo tree search (MCTS) is an AI technique that has been successfully applied to
many deterministic games of perfect information. This paper investigates the application of …
many deterministic games of perfect information. This paper investigates the application of …
Automated video game testing using synthetic and humanlike agents
In this article, we present a new methodology that employs tester agents to automate video
game testing. We introduce two types of agents-synthetic and humanlike-and two distinct …
game testing. We introduce two types of agents-synthetic and humanlike-and two distinct …
On monte carlo tree search and reinforcement learning
Fuelled by successes in Computer Go, Monte Carlo tree search (MCTS) has achieved wide-
spread adoption within the games community. Its links to traditional reinforcement learning …
spread adoption within the games community. Its links to traditional reinforcement learning …
Trial-based heuristic tree search for finite horizon MDPs
Dynamic programming is a well-known approach for solving MDPs. In large state spaces,
asynchronous versions like Real-Time Dynamic Programming have been applied …
asynchronous versions like Real-Time Dynamic Programming have been applied …
Ensemble determinization in monte carlo tree search for the imperfect information card game magic: The gathering
In this paper, we examine the use of Monte Carlo tree search (MCTS) for a variant of one of
the most popular and profitable games in the world: the card game Magic: The Gathering (M …
the most popular and profitable games in the world: the card game Magic: The Gathering (M …