Games of timing reflect dynamic decision-making under uncertainty, as it takes place in many real-world situations, including health care, safety and security. Rather than making discrete decisions, participants choose one or more points in time that determine the outcome. We study individual’s biases and characteristics in such games of timing. We examine risk propensity as a personal preferen...

Opponent behavior in today's computer games is often the result of a static set of Artificial Intelligence (AI) behaviors or a fixed AI script. While this ensures that the behavior is reasonably intelligent, it also results in very predictable behavior. This can have an impact on the replayability of entertainment-based games and the educational value of training-based games. This paper propose...

This chapter arises from the discussions of an experienced international group of researchers interested in the potential for creative application of algorithms for searching finite discrete graphs, which have been highly successful in a wide range of application areas, to address a broad range of problems arising in video games. The chapter first summarises the state of the art in search algor...

This chapter arises from the discussions of an experienced international group of researchers interested in the potential for creative application of algorithms for searching finite discrete graphs, which have been highly successful in a wide range of application areas, to address a broad range of problems arising in video games. The chapter first summarises the state of the art in search algor...

Real-time strategy (RTS) games are hard from an AI point of view because they have enormous state spaces, combinatorial branching factors, allow simultaneous and durative actions, and players have very little time to choose actions. For these reasons, standard game tree search methods such as alphabeta search or Monte Carlo Tree Search (MCTS) are not sufficient by themselves to handle these gam...

In this article, a class of continuous-time noncooperative games in networks double-integrator agents is explored. The existing methods require that communicate with their neighbors real time. we propose two discrete-time communication schemes based on the designed strategy-updating rule for efficient use resources. First, property analyzed to ensure all agents’ strategies can reach Nash equili...

In this paper we compare different machine learning algorithms to predict the outcome of 2 player games in StarCraft, a wellknown Real-Time Strategy (RTS) game. In particular we discuss the game state representation, the accuracy of the prediction as the game progresses, the size of the training set and the stability of the predictions.

Explanations can play a key role in case-based planning systems. We describe an application of hierarchical case-based planning that involves reasoning in the context of real-time strategy games , describe a representation for explanations in this context, and detail four types of explanations.

This article1 motivates AI research in the area of real–time strategy (RTS) games and describes the current status of the ORTS project whose goals are to implement an RTS game programming environment and to build AI systems that eventually can outperform human experts in this popular and challenging domain.

We analyze evolutionary games with replicator dynamics that have frequency dependent stage games. In such an evolutionary game, the payoffs of a strategy at any point in time are functions of the strategy shares given by the players’ strategy choices at that time. This framework is suited to model feedback effects between population variables and individual incentives, indirect network effects,...