Common knowledge of intentions is crucial to basic social tasks ranging from cooperative hunting to oligopoly collusion, riots, revolutions, and the evolution of social norms and human culture. Yet little is known about how common knowledge leaves a trace on the dynamics of a social network. Here we show how an individual’s network properties—primarily local clustering and betweenness centralit...

We propose d-stag, a new formalism for the automatic analysis of discourse. The analyses computed by d-stag are hierarchical discourse structures annotated with discourse relations, which are compatible with discourse structures computed in sdrt. A discursive stag grammar pairs up trees anchored by discourse connectives with trees anchored by (functors associated with) discourse relations.

Recent work has used the synchronous tree-adjoining grammar (STAG) formalism to demonstrate that many of the cases in which syntactic and semantic derivations appeared to be divergent could be handled elegantly through synchronization. This research has provided syntax and semantics for diverse and complex linguistic phenomena. However, certain hard cases push the STAG formalism to its limits, ...

Synchronous Tree-Adjoining Grammar (STAG) is a promising formalism for syntaxaware machine translation and simultaneous computation of natural-language syntax and semantics. Current research in both of these areas is actively pursuing its incorporation. However, STAG parsing is known to be NP-hard due to the potential for intertwined correspondences between the linked nonterminal symbols in the...

The kinetics of the humoral immune response was evaluated using the recombinant SAG2A protein comparatively to soluble Toxoplasma antigen (STAg) by ELISA in sequential serum samples of patients with toxoplasmosis up to 12 months of illness onset. The follow up of IgM and IgA levels to STAg showed a gradual decrease, with the majority of patients (88%) seropositive for IgM up to 12 months of inf...

Deep reinforcement learning has become an important paradigm for constructing agents that can enter complex multi-agent situations and improve their policies through experience. One commonly used technique is reactive training applying standard RL methods while treating other agents as a part of the learner’s environment. It is known that in general-sum games reactive training can lead groups o...