in the past, science was not as specialized as it currently is and scientists mastered miscellaneous sciences. currently, human sciences are inter-related with mutual connections that have mutual effects with respect to defining their key themes. in this regard, the present study, while explaining the concept of business competition, which is among the key issues in economics,has sought to inve...

Reinforcement Learning (RL) of trajectory data has been used in several fields, and it is relevance robot motion learning, which sampled trajectories are run their outcome evaluated with a reward value. The responsibility on the performance task can be associated to as whole, or distributed throughout its points (timesteps). In this work, we present novel method for attributing rewards each tim...

We present a characterization of the set non-signaling correlations in terms two dimensional representation that involves maximal value Bell functional and mutual information between parties. In particular, we apply this to bipartite scenario with measurements outcomes. these physically meaningful quantities through numerical optimization methods some analytical results, investigate frontier di...

The narrative cloze is an evaluation metric commonly used for work on automatic script induction. While prior work in this area has focused on count-based methods from distributional semantics, such as pointwise mutual information, we argue that the narrative cloze can be productively reframed as a language modeling task. By training a discriminative language model for this task, we attain impr...

Topic models can learn topics that are highly interpretable, semantically-coherent and can be used similarly to subject headings. But sometimes learned topics are lists of words that do not convey much useful information. We propose models that score the usefulness of topics, including a model that computes a score based on pointwise mutual information (PMI) of pairs of words in a topic. Our PM...