Punishing Collective Entities

Punishing Collective Entities

Relational Learning for Collective Classification of Entities in Images

We consider the problem of discrete multi-label entity classification in images. We argue that the framework of Markov Logic can provide a unified, well-grounded mechanism to incorporate arbitrary logical relationships between entities to improve classification in images, and thus generalizes much of the recent work on exploiting local and global context in object recognition and scene understa...

Collective Segmentation and Labeling of Distant Entities in Information Extraction

In information extraction, we often wish to identify all mentions of an entity, such as a person or organization. Traditionally, a group of words is labeled as an entity based only on local information. But information from throughout a document can be useful; for example, if the same word is used multiple times, it is likely to have the same label each time. We present a CRF that explicitly re...

Punishing greediness in Divide-the-dollar games

Brams and Taylor (1994) presented a version of the Divide-the-dollar game (DD), which they call DD1. DD1 suffers from the following drawback: when each player demands approximately the entire dollar, then if the least greedy player is unique, then this player obtains approximately the entire dollar even if he is only slightly less greedy than the other players. I introduce a parametrized family...

Punishing and abstaining for public goods.

The evolution of cooperation within sizable groups of nonrelated humans offers many challenges for our understanding. Current research has highlighted two factors boosting cooperation in public goods interactions, namely, costly punishment of defectors and the option to abstain from the joint enterprise. A recent modeling approach has suggested that the autarkic option acts as a catalyzer for t...