Moshe Bitan

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People’s facial expressions, whether made consciously or subconsciously, continuously reveal their state of mind. This work proposes a method for predicting people’s strategic decisions based on their facial expressions. We designed a new version of the centipede game that intorduces an incentive for the human participant to hide her facial expressions. We(More)
Despite committees and elections being widespread in the real-world, the design of agents for operating in humancomputer committees has received far less attention than the theoretical analysis of voting strategies. We address this gap by providing an agent design that outperforms other voters in groups comprising both people and computer agents. In our(More)
In this paper, we present a Virtual-Suspect system which can be used to train inexperienced law enforcement personnel in interrogation strategies. The system supports different scenario configurations based on historical data. The responses presented by the Virtual-Suspect are selected based on the psychological state of the suspect, which can be configured(More)
Monte Carlo Tree Search (MCTS) has been extended to many imperfect information games. However, due to the added complexity that uncertainty introduces, these adaptations have not reached the same level of practical success as their perfect information counterparts. In this paper we consider the development of agents that perform well against humans in(More)
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