A mentalist agent for identifying characters using dynamic query strategies
Adrian Petru Groza, Loredana Coroama · 2019
We consider the problem of finding the minimal sequence of questions needed to identify an unknown element from a set of cardinality M. This task is common meet in games such as Guess Who, 20 Questions or Akinator. Our scenario is to identify a person based on features extracted from an image. The assumption is that the user thinks at any person described on the DBpedia. We do not store previous expert knowledge or user profile. The sequence of questions is built based on heuristics that favor the most relevant features: information gain, gain ration, probabilistic entropy. As we deal with features that are automatically extracted from images, the data is noisy. We test the performance of the method using simulated dialogues between software agent and human agent.